Job Title: AI Engineer Company: Franklin Templeton Job Category: Machine Learning Roles & Responsibilities: About The Department * Lexington Partners’ Data and AI team designs and delivers data, analytics, and GENAI solutions that help drive business performance across the organization. Working closely with business and technology stakeholders, the team develops innovative tools, enhances data capabilities, and integrates AI into existing digital platforms. Team members gain exposure to cutting\-edge technologies, meaningful business challenges, and opportunities to influence the future of AI adoption within a global investment firm. How You Will Add Value?* Core Responsibilities * You will design and develop GENAI solutions. * You will build scalable and reliable AI applications. * You will create proof\-of\-concepts to validate new technologies. * You will evaluate model performance and business value. * You will integrate AI into existing workflows. * You will support business teams with practical solutions. * You will maintain and improve deployed applications. Strategic Responsibilities * You will research emerging AI technologies. * You will identify opportunities for innovation and automation. * You will recommend new approaches and capabilities. * You will contribute to AI product direction. * You will help shape long\-term technology strategy. Team \& Collaboration * You will partner with business and technology stakeholders. * You will analyze and prepare data for model development. * You will train and optimize AI models. * You will document solutions and technical processes. * You will present findings and recommendations. * You will communicate project progress regularly. * You will take ownership of end\-to\-end project delivery. Work Shift Timings \- 2:00 PM \- 11:00 PM IST Work Location: Greater Hyderabad Area Availability: Full time

Job Title: Senior Machine Learning Engineer Company: Epic Games Job Category: Machine Learning Roles & Responsibilities: Being Epic means being a part of a team that continually strives to do right by our community and users. We’re constantly innovating to raise the bar of engine and game development. What We Do Unreal projects have been leading the pack of real\-time entertainment with our constantly growing team of engineering experts. We’re always improving on the tools and technology that empower content developers worldwide. What You'll Do You will work with our team of applied research engineers at the intersection of computer vision, gameplay agents, natural language processing, and machine learning to create state\-of\-the\-art tools to support game developers in our ecosystem with a focus on bots (trained gameplay agents, intelligent NPCs, companions, world modeling), as well as automation of a number key areas (including moderation, security, and QA testing). You will be responsible for the design, implementation and deployment of production\-ready machine learning models that can be integrated in our ecosystem. In this role, you will * Create and deliver production\-ready, scalable and high\-quality machine learning models and associated algorithms that can make actions in game environments * Critically assess the effectiveness of such models and make recommendations for the ongoing roadmap * Methodically understand and assess the effectiveness of new data channels and support collection/creation of new ones About Us Epic Games is a leading interactive entertainment company. For over 30 years we've been making award\-winning games and engine technology that empowers others to make visually stunning games and 3D content that bring environments to life like never before. Epic's award\-winning Unreal Engine technology not only provides game developers the ability to build high\-fidelity, interactive experiences for PC, console, mobile, and VR, it is also a tool being embraced by content creators across a variety of industries such as media and entertainment, automotive, and architectural design. As we continue to build our Engine technology and develop remarkable games, we strive to build teams of world\-class talent. Work Location: Greater London, England, UK Availability: Full time

Job Title: Software Engineer (Mid and Senior Levels) Company: One Big Circle Job Category: Machine Learning Roles & Responsibilities: We are looking for a proactive and motivated individual to join our team to support the business in further growing our flagship award\-winning product: AIVR. AIVR (Automated Intelligent Video Review) is a state\-of\-the\-art video technology system used by thousands of people in the rail industry. AIVR has won dozens of awards and is recognised as the market leading solution, but we are building many more opportunities both in existing and new markets which will further accelerate our growth. We have built a culture where people feel supported, included, and empowered to do their best work. Our team is growing, and we’d love for you to be part of the journey. Available Roles Cloud infrastructure, AWS, distributed systems, backend services, RESTful APIs, microservices architecture, service integration, data pipelines, storage systems, relational databases (MySQL), scalability, system reliability, observability, infrastructure as code, serverless deployments, containerisation (Docker), AWS services (Lambda, SQS, EC2, S3\), IAM permissions (AWS), DevOps security, CI/CD, CI/CD tools (GitHub Workflows), Git, Python development, Python testing frameworks (pytest, unittest), JavaScript knowledge (Node.js), RabbitMQ, FFMPEG, Linux systems administration Applied machine learning, computer vision, object detection, image classification, model development and evaluation, data annotation and curation, training pipelines, performance optimisation, edge ML, MLOps, deployment and maintenance of ML solutions, Python development, Python\-based ML frameworks, PyTorch, TensorFlow, sklearn, OpenCV, NumPy, feature development, code review, pytest, linting, bug fixing, relational databases, database design and maintenance, AWS/cloud infrastructure, CI/CD pipelines, developer tooling, Linux systems The Role As an OBC Software Engineer, you’ll be a hands\-on contributor, working closely with experienced engineers to build reliable, high\-performance systems across devices, cloud platforms, and applied ML, contributing to real\-world, field\-deployed solutions. You will take responsibility for defined components and projects, contributing to system design, implementation, testing, and deployment, while continuing to develop your technical and professional skills. Responsibilities You will contribute to the development of innovative solutions within a skilled team that likes getting things done: * Design, develop, and maintain software solutions * Contribute to system design and technical decision\-making within the team * Collaborate with adjacent teams to achieve system integration * Take ownership of features, projects, or technical areas (scope matched to experience) * Diagnose and resolve issues with in\-service systems and data * Contribute to code reviews and help maintain high engineering standards * Support continuous improvement of development practices, tooling, and system reliability * Practical and delivery\-focused, balancing engineering rigour with pragmatism * Strong communication skills, able to work effectively with multidisciplinary teams * Self\-motivated and proactive, with a willingness to take ownership of work * Comfortable contributing to code reviews and technical discussions * Willing to support more junior engineers * Keen to grow into greater responsibility for technical direction and project delivery * Auto enrolment Pension Scheme * 25 Days Holiday plus bank holidays * Life Assurance * Private Healthcare Cover * Work related training courses as required * Complimentary snacks and refreshments including fresh fruit * Office\-Centric role * Access to Bike to Work Scheme * Secure bike storage and shower facilities * Social events Please visit our careers page at onebigcircle.co.uk/careers to view our full list of current vacancies, including similar roles that may be of interest. By applying for this role, you understand that we will process your personal information in accordance with our privacy policy, accessible at https://onebigcircle.co.uk/privacy\-policy/ Work Location: In person Work Location: Bristol, ENG, UK Availability: Full time

Job Title: Machine Learning Engineer Company: Xantura Limited Job Category: Machine Learning Roles & Responsibilities: In this role you will work in the Platform team – a function for the deployment and evolution of the backend platform that underpins the core of the Xantura business. Key Responsibilities * Own and advance a predictive modelling platform that scales across problem types and tenants, using it to design, implement, and iterate models (embedding\-based sequence encoders, temporal survival models, gradient\-boosted decision trees) that predict key vulnerabilities in housing, health, and other social domains. * Track developments in ML and frontier models, running structured experiments to bring promising techniques into production safely. * Build robust evaluation pipelines, training datasets, and model infrastructure to support continuous improvement of natural language \& predictive analytics. * Ensure responsible AI deployment, embedding ethical and regulatory considerations into every stage of development. * Mental health and wellbeing support * Remote GP access * Counselling/therapy * Physiotherapy * Medical second opinions Work Location: Greater London, England, UK Availability: Full time

Job Title: Senior Software Engineer, GenAI Platform Company: Deliveroo Job Category: Machine Learning Roles & Responsibilities: Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we're unlocking new possibilities as one global team. About the Role ------------------ You will join a small, high\-leverage team building production infrastructure for Generative AI at Deliveroo and DoorDash, leading the design and architecture of our open\-weights model platform spanning inference and fine\-tuning: real\-time GPU serving, high\-throughput batch inference, and model fine\-tuning. You'll set technical direction across model serving and inference engines, fine\-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ambiguous, high\-impact systems and pushing the cost/performance frontier of GPU inference and fine\-tuning in a fast\-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly. * Lead the design of infrastructure that helps teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. * Own and evolve our open\-weights serving stack — real\-time GPU endpoints, high\-throughput batch inference, and fine\-tuning (SFT/DPO/LoRA) — alongside the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. * Architect scalable, high\-performance systems for model serving, batch inference, GPU autoscaling, and fine\-tuning that power real customer and internal automation use cases * Push the cost and latency frontier of GPU inference — turning batch jobs that took days into hours and cutting inference cost by multiples — while giving product teams a clean choice across open\-weight and closed\-source models with reliability, fallback, observability, and cost controls built in. * Build platforms that support rapid experimentation while meeting production standards for latency, scale, monitoring, SLOs, playbooks, and operational excellence. * Partner closely with — and raise the technical bar for — ML engineers, product engineers, data scientists, and platform teams across DoorDash, Wolt, and Deliveroo to turn emerging GenAI capabilities into durable platform primitives. * Set technical direction for the future of the company's centralised GenAI platform — including emerging directions such as reinforcement learning (RLHF/RLVR), agent optimisation, and other post\-training and agentic techniques — enabling the next generation of AI\-powered products, agents, automation, and personalisation. * BSc, MSc or PhD in Computer Science or equivalent * 5\+ years of industry experience in software engineering * Deep backend engineering fundamentals, especially in Python and distributed systems. * Track record of designing and owning production services, APIs, data pipelines, or ML infrastructure at scale. * Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization. * Deep hands\-on experience with LLM inference and/or fine\-tuning of open\-weight models in production — serving (latency, throughput, batching, autoscaling, GPU utilization) and/or fine\-tuning (SFT/DPO/LoRA). * Demonstrated technical leadership: leading design across ambiguous, fast\-moving technical areas, mentoring engineers, and turning customer use cases into reusable platform capabilities * Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software If you have a disability or long\-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you'll have the opportunity to let us know once you've submitted your application. We'll share details on how to request support so we can ensure you have a fair and equitable experience. If you're excited about making a real impact in a fast\-moving marketplace and growing your career alongside ambitious, supportive teams, we'd love to hear from you! Work Location: London, ENG, UK Availability: Full time

Job Title: Applied AI ML - Senior Associate - Machine Learning Engineer Company: JPMorganChase Job Category: Machine Learning Roles & Responsibilities: Job Description Join a high performing team of applied AI experts to drive innovation and new capabilities in the Commercial \& Investment Bank. As an Applied AI / ML Senior Associate Machine Learning Engineer in the Applied AI ML team at JPMorgan Commercial \& Investment Bank, you will be at the forefront of combining cutting\-edge AI techniques with the company's unique data assets to optimize business decisions and automate processes. You will have the opportunity to advance the state\-of\-the\-art in AI as applied to financial services, leveraging the latest research from fields of Natural Language Processing, Computer Vision, and statistical machine learning. You will be instrumental in building products that automate processes, help experts prioritize their time, and make better decisions. We have a growing portfolio of AI–powered products and services and increasing opportunity for re\-use of foundational components through careful design of libraries and services to be leveraged across the team. This role offers a unique blend of scientific research and software engineering, requiring a deep understanding of both mindsets. Job Responsibilities * Build robust Data Science capabilities which can be scaled across multiple business use cases * Collaborate with software engineering team to design and deploy Machine Learning services that can be integrated with strategic systems * Research and analyse data sets using a variety of statistical and machine learning techniques * Communicate AI capabilities and results to both technical and non\-technical audiences * Document approaches taken, techniques used and processes followed to comply with industry regulation * Collaborate closely with cloud and SRE teams while taking a leading role in the design and delivery of the production architectures for our solutions. * Act as an individual contributor, though there will be optional opportunity for management responsibility dependent on the candidate's experience. About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first\-class business in a first\-class way approach to serving clients drives everything we do. We strive to build trusted, long\-term partnerships to help our clients achieve their business objectives. About The Team J.P. Morgan's Commercial \& Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial \& Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. Work Location: Greater London, England, UK Availability: Full time

Job Title: Applied AI ML Data Scientist, Vice President - Payments Company: JPMorganChase Job Category: Machine Learning Roles & Responsibilities: Job Description Payments sit at the center of the global economy, connecting businesses and consumers around the world. You will join a team driving innovation in this fast evolving space as new technologies reshape how money moves. In this role, you will work at the forefront of modern machine learning and generative AI to deliver meaningful, lasting impact on global finance. You will partner closely with product, operations, risk, and technology teams to turn ideas into measurable outcomes. You will also have opportunities to mentor others and help shape how we build and operate production AI. As a Vice President Machine Learning Data Scientist in Payments Machine Learning, you will lead the design, development, and production deployment of machine learning applications, including generative AI and agentic systems, on cloud infrastructure. You will own end\-to\-end delivery from problem framing and experimental design through scalable MLOps, evaluation, governance, and integration with strategic systems. You will help set technical direction, establish reusable patterns, and ensure solutions are reliable, secure, and observable in production. You will mentor engineers and data scientists and translate complex technical work into clear decisions and outcomes for stakeholders. Job Responsibilities * Lead end\-to\-end delivery of machine learning and AI solutions for complex payments and banking operations problems, from discovery and framing to production rollout and lifecycle management * Develop innovative machine learning solutions, including generative AI and multi\-agent approaches, and define evaluation, safety, and monitoring strategies for production use * Own production deployment patterns including containerization, continuous integration and delivery, automated testing, model and prompt registries, model and version governance, monitoring and alerting, and rollback strategies * Architect and deploy scalable, reliable, and secure machine learning and large language model services integrated with strategic platforms and downstream consumers across APIs, batch, streaming, and event\-driven patterns, meeting service level objectives * Partner with product, operations, risk and control, and technology teams to influence roadmaps, align on requirements, and deliver data\-led transformations * Establish reusable, modular data science and machine learning capabilities that scale across use cases, including feature engineering, evaluation harnesses, prompt tooling patterns, agent frameworks, orchestration, and context and memory management * Provide technical leadership and mentorship through code reviews, design reviews, best practices, and upskilling across data science and engineering partners * Communicate with technical and non\-technical stakeholders, translating model outputs into decisions, tradeoffs, and operational plans * Maintain strong documentation for approaches, model cards, runbooks, and operational procedures About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first\-class business in a first\-class way approach to serving clients drives everything we do. We strive to build trusted, long\-term partnerships to help our clients achieve their business objectives. About The Team J.P. Morgan's Commercial \& Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial \& Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. Work Location: Greater London, England, UK Availability: Full time

Job Title: Head of Data Analytics Company: GoTyme ZA (South Africa) Job Category: Machine Learning Roles & Responsibilities: Role Purpose ---------------- The Head of Data Analytics leads GoTyme Bank's business\-facing data science capability across Marketing, Fraud, AML, Customer Experience, Distribution and Partnerships. You will turn company and functional priorities into a clear analytics roadmap, lead and develop a team of data scientists and senior data scientists, and ensure that the team's work changes decisions and improves measurable business outcomes. This is a senior people and delivery leadership role with strong technical credibility. You will move the function from reactive request fulfilment towards proactive insight, experimentation and responsible use of advanced analytics and AI. You will work closely with Reporting and Insights, Data Governance, Data Engineering, Finance, Risk, Product and Lending Analytics so that decision makers receive trusted, timely and well\-governed analysis. Key Responsibilities ------------------------ * Analytics Strategy and Business Impact * + Set and own the data analytics strategy and roadmap for the functions in scope, aligned to GoTyme Bank's company priorities and measurable business outcomes. + Direct proactive analysis across customer acquisition, activation, engagement, segmentation, revenue, fraud prevention, AML effectiveness, customer experience, distribution performance and partner value. + Frame the right business questions, identify opportunities before they become requests, and ensure insights are translated into decisions, actions and measurable impact. + Establish clear success measures for major analytics initiatives and track whether recommendations are adopted and deliver the intended result. * People Leadership and Capability * + Act as the primary line manager for data scientists and senior data scientists within the function, owning performance, development and day\-to\-day effectiveness. + Recruit, onboard, coach and retain strong analytical talent; set clear expectations and provide regular, honest and developmental feedback. + Build succession and capability plans, create opportunities for team members to take on greater responsibility, and address performance or capability gaps early. + Create a team environment where people collaborate across domains, share knowledge, raise risks openly and maintain high standards without losing pace. * Prioritisation Planning and Delivery * + Run a transparent intake and prioritisation process so that analytical capacity is directed to the highest\-value work across the functions in scope. + Maintain a visible roadmap, stakeholder service levels and a regular operating cadence covering delivery, impact, capacity, risks and dependencies. + Own the quality and timeliness of the team's output; resolve blockers, coordinate cross\-team dependencies and escalate trade\-offs early when capacity or priorities conflict. + Clarify ownership and hand\-offs with Reporting and Insights, Data Governance, Data Engineering and Lending Analytics to avoid duplicated work or gaps in delivery. * Stakeholder Leadership * + Act as the senior analytics partner for Marketing, Fraud, AML, Customer Experience, Distribution and Partnerships, building trusted relationships with functional leaders and their teams. + Communicate analytical strategy, evidence, trade\-offs and recommendations clearly to executive, commercial, risk and technical audiences. + Represent Data Analytics in relevant governance, planning and performance forums, ensuring that evidence is used in material decisions. + Challenge assumptions constructively, establish common definitions and help stakeholders distinguish useful analysis from activity that will not change a decision. * Analytical Standards Experimentation and Innovation * + Set consistent standards for analytical design, SQL and Python development, peer review, documentation, reproducibility, quality assurance and communication of results. + Build disciplined test\-and\-learn practices for campaigns, customer journeys, fraud controls, segmentation, channel interventions and partner initiatives. + Apply advanced analytics, machine learning and generative AI where they can improve decisions, turnaround time or efficiency, with clear measures of value and appropriate human oversight. + Partner with platform, engineering and reporting teams to create reusable data products, scalable analytical assets and well\-governed self\-service capabilities. * Governance Risk and Compliance * + Ensure that the function complies with data governance, privacy, information security, model governance and regulatory requirements, including appropriate access controls and audit trails. + Maintain documented review and monitoring processes for analytical outputs used in customer, risk, executive or regulatory decisions. + Identify and escalate material data quality, bias, control or interpretation risks, and ensure agreed remediation is completed. + Support audit and regulatory requests relevant to the function and ensure that all team members complete required compliance training. * 2 years of experience in data science, business analytics or a related quantitative field, including substantial people leadership responsibility. * Demonstrated success leading senior analytical talent and delivering high\-quality work through teams rather than relying on personal contribution alone. * Track record of using analytics to improve commercial, customer, operational or risk outcomes in a complex organisation. * Experience managing a portfolio of competing work and influencing senior stakeholders when priorities, capacity or evidence are contested. * Strong technical grounding in statistics, experimentation, predictive modelling and data science, with current proficiency in SQL and Python sufficient to review and guide the team's work. * Commercial judgement and the ability to connect analytical work to customer, revenue, cost, risk, control and service outcomes. * Strong people leadership across performance management, coaching, feedback, hiring and career development. * Clear, structured communication across technical and non\-technical audiences, including executive\-level recommendations and difficult stakeholder conversations. * Strong prioritisation, portfolio planning and delivery management, with the ability to make transparent decisions under ambiguity and capacity constraints. * Sound understanding of data quality, privacy, analytical governance and the controls required in a regulated environment. * Experience in retail banking, fintech or another regulated consumer business. * Domain experience in more than one of marketing analytics, customer analytics, fraud, financial crime, distribution analytics or partner data. * Experience with modern cloud analytics platforms such as Databricks and with team\-based development practices including Git and code review. * Experience with analytical governance, model risk, regulatory reporting, audit remediation or privacy requirements such as POPIA. * Experience leading teams through organisational change, rapid growth or a shift from reactive requests to proactive analytics. * People\-first leader who invests in the growth, performance and wellbeing of the team. * Proactive and commercially curious; looks for important questions and opportunities rather than waiting for a request. * Pragmatic and evidence\-led; balances analytical rigour with pace, capacity and business need. * Direct and fair; gives clear feedback, handles difficult conversations and makes trade\-offs visible. * Calm and dependable under pressure, providing structure and direction when priorities are ambiguous or changing. * Collaborative across functions and willing to challenge constructively when the evidence requires it. * EAP support (counselling, financial and legal for you and anyone financially dependent on you). * Competitive, industry\-benchmarked salaries. * Non\-guaranteed performance bonuses. * Access to company shares (T's \& C's apply). * Wellness days. * Social clubs. * On\-site barista. Work Location: Johannesburg, GP, South Africa Availability: Full time

Job Title: Quantitative Analyst Company: Nedbank Job Category: Machine Learning Roles & Responsibilities: Leadership Pipeline Manage Self: Professional FAIS Affected Job Purpose Support the development, refinement, testing, deployment, and maintenance of quantitative models, dashboards, and analytics solutions in accordance with group methodologies and/or industry best practices. Build foundational expertise in data science, risk modelling, and commercial acumen to enable independent delivery of high\-impact solutions across the Nedbank value chain. They support senior quantitative analytics teams by collecting, cleaning, and analysing data that forms the foundation for complex quantitative solutions. Job Responsibilities Domain and Technical Expertise * Acquire and continuously develop/improve deep expertise in banking products, services and risk management. * Acquire and continuously develop/improve deep domain expertise in quantitative analytics and their application across various risk types and specialised functional. * Conduct research and analysis to build, maintain and continuously refine mathematical and statistical models and quantitative solutions. Collaboration and Development * Leverage mentorship and guidance from Senior Quantitative analysts and the broader quantitative teams regarding best practices and research to calibrate and validate model and quantitative solution components. * Collaborate with senior quantitative analysts to commercialise quantitative models and embed them into production systems. Model Design and Development * Contribute to the build and maintenance of domain specific models and quant solutions (e.g. credit, pricing, market risk, trading, liquidity, impairments). * Apply statistical and machine learning techniques to extract insights and improve model performance. * Ensure accuracy and stability of quantitative solutions and models (and or contributions) while considering the business impact. * Contribute to testing of components of complex quantitative solutions using multiple testing methods (e.g. back testing, stress testing, unit testing, integration testing, system testing, regression, black box, sanity, conformance, acceptance, forward etc.). * Analyse quantitative solutions or statistical models (e.g. machine learning, NLP, etc.) outputs using various techniques and methodologies. * Engineer and validate large datasets for model consumption, ensuring quality and integrity. Delivery management * Work and collaborate within and across teams, senior analysts and digital/technology teams to develop, maintain, enhance and deploy scalable models. * Support senior analysts and broader quantitative teams in the business change management and capability development processes related to the deployment of model/quantitative solutions. * Ensure agile delivery, cross functional collaboration and deployment readiness of models. Job Responsibilities Continue People * Participate in multi\-disciplinary/cross functional/business teams to design and deploy quant solutions. * Provide and receive peer reviews and constructive feedback. * Adopt a development mindset, demonstrating commitment, learning agility and an independent drive for continuous improvement and growth towards independent design and delivery of quantitative solutions. * Participate as a member of agile teams (sometimes multiple simultaneously) and deliver within continuously evolving strategic contexts and domain areas. * Actively contribute to a culture of innovation and continuous learning within the greater quant community. Governance, Risk and Finance * Comply with both internal risk governance frameworks and external regulations, ensuring both integrity of quantitative solutions developed and adherence to conduct requirements (e.g., independence between model development and validation, SAS MRM Standards.) * Develop an understanding of the regulatory requirements and various standards (e.g. IFRS, Basel, etc.), ensuring their effective implementation in all relevant quantitative solutions and model development processes. * Participate in and provide technical support for the remediation of regulatory, validation, peer review, and audit findings. * Support model risk mitigation through robust validation, monitoring and remediation practices Technical / Professional Knowledge * Demonstrates foundational understanding of quantitative methods and apply them to defined tasks; more complex analyses are completed with guidance and supervision. * Strong knowledge of probability and statistics * Technical understanding or exposure to statistical analysis and models * Strong analytical and problem\-solving skills and ability to translate complex data and model / solution outcomes into business insights. * Proficiency or familiarity in programming languages (e.g. Python, R, C\+\+, Java, SQL, SAS, VBA, MATLAB, etc.), with the ability to translate algorithms and mathematical or statistical models into flexible and scalable coding logic * Technical understanding or exposure to big data concepts, data structures, data storage, data extraction/mining. * Technical understanding or exposure of model lifecycle management i.e. development, validation, implementation, monitoring. * Technical understanding and exposure to AI/ML techniques and model explainability tools (e.g., SHAP, LIME etc.). * Some exposure to banking regulation and accounting standards preferred but not essential Work Location: Johannesburg, Gauteng, South Africa Availability: Full time

Job Title: Head of Data Analytics Company: GoTyme ZA (South Africa) Job Category: Machine Learning Roles & Responsibilities: Role Purpose ---------------- The Head of Data Analytics leads GoTyme Bank's business\-facing data science capability across Marketing, Fraud, AML, Customer Experience, Distribution and Partnerships. You will turn company and functional priorities into a clear analytics roadmap, lead and develop a team of data scientists and senior data scientists, and ensure that the team's work changes decisions and improves measurable business outcomes. This is a senior people and delivery leadership role with strong technical credibility. You will move the function from reactive request fulfilment towards proactive insight, experimentation and responsible use of advanced analytics and AI. You will work closely with Reporting and Insights, Data Governance, Data Engineering, Finance, Risk, Product and Lending Analytics so that decision makers receive trusted, timely and well\-governed analysis. Key Responsibilities ------------------------ * Analytics Strategy and Business Impact * + Set and own the data analytics strategy and roadmap for the functions in scope, aligned to GoTyme Bank's company priorities and measurable business outcomes. + Direct proactive analysis across customer acquisition, activation, engagement, segmentation, revenue, fraud prevention, AML effectiveness, customer experience, distribution performance and partner value. + Frame the right business questions, identify opportunities before they become requests, and ensure insights are translated into decisions, actions and measurable impact. + Establish clear success measures for major analytics initiatives and track whether recommendations are adopted and deliver the intended result. * People Leadership and Capability * + Act as the primary line manager for data scientists and senior data scientists within the function, owning performance, development and day\-to\-day effectiveness. + Recruit, onboard, coach and retain strong analytical talent; set clear expectations and provide regular, honest and developmental feedback. + Build succession and capability plans, create opportunities for team members to take on greater responsibility, and address performance or capability gaps early. + Create a team environment where people collaborate across domains, share knowledge, raise risks openly and maintain high standards without losing pace. * Prioritisation Planning and Delivery * + Run a transparent intake and prioritisation process so that analytical capacity is directed to the highest\-value work across the functions in scope. + Maintain a visible roadmap, stakeholder service levels and a regular operating cadence covering delivery, impact, capacity, risks and dependencies. + Own the quality and timeliness of the team's output; resolve blockers, coordinate cross\-team dependencies and escalate trade\-offs early when capacity or priorities conflict. + Clarify ownership and hand\-offs with Reporting and Insights, Data Governance, Data Engineering and Lending Analytics to avoid duplicated work or gaps in delivery. * Stakeholder Leadership * + Act as the senior analytics partner for Marketing, Fraud, AML, Customer Experience, Distribution and Partnerships, building trusted relationships with functional leaders and their teams. + Communicate analytical strategy, evidence, trade\-offs and recommendations clearly to executive, commercial, risk and technical audiences. + Represent Data Analytics in relevant governance, planning and performance forums, ensuring that evidence is used in material decisions. + Challenge assumptions constructively, establish common definitions and help stakeholders distinguish useful analysis from activity that will not change a decision. * Analytical Standards Experimentation and Innovation * + Set consistent standards for analytical design, SQL and Python development, peer review, documentation, reproducibility, quality assurance and communication of results. + Build disciplined test\-and\-learn practices for campaigns, customer journeys, fraud controls, segmentation, channel interventions and partner initiatives. + Apply advanced analytics, machine learning and generative AI where they can improve decisions, turnaround time or efficiency, with clear measures of value and appropriate human oversight. + Partner with platform, engineering and reporting teams to create reusable data products, scalable analytical assets and well\-governed self\-service capabilities. * Governance Risk and Compliance * + Ensure that the function complies with data governance, privacy, information security, model governance and regulatory requirements, including appropriate access controls and audit trails. + Maintain documented review and monitoring processes for analytical outputs used in customer, risk, executive or regulatory decisions. + Identify and escalate material data quality, bias, control or interpretation risks, and ensure agreed remediation is completed. + Support audit and regulatory requests relevant to the function and ensure that all team members complete required compliance training. * 0-2 years of experience in data science, business analytics or a related quantitative field, including substantial people leadership responsibility. * Demonstrated success leading senior analytical talent and delivering high\-quality work through teams rather than relying on personal contribution alone. * Track record of using analytics to improve commercial, customer, operational or risk outcomes in a complex organisation. * Experience managing a portfolio of competing work and influencing senior stakeholders when priorities, capacity or evidence are contested. * Strong technical grounding in statistics, experimentation, predictive modelling and data science, with current proficiency in SQL and Python sufficient to review and guide the team's work. * Commercial judgement and the ability to connect analytical work to customer, revenue, cost, risk, control and service outcomes. * Strong people leadership across performance management, coaching, feedback, hiring and career development. * Clear, structured communication across technical and non\-technical audiences, including executive\-level recommendations and difficult stakeholder conversations. * Strong prioritisation, portfolio planning and delivery management, with the ability to make transparent decisions under ambiguity and capacity constraints. * Sound understanding of data quality, privacy, analytical governance and the controls required in a regulated environment. * Experience in retail banking, fintech or another regulated consumer business. * Domain experience in more than one of marketing analytics, customer analytics, fraud, financial crime, distribution analytics or partner data. * Experience with modern cloud analytics platforms such as Databricks and with team\-based development practices including Git and code review. * Experience with analytical governance, model risk, regulatory reporting, audit remediation or privacy requirements such as POPIA. * Experience leading teams through organisational change, rapid growth or a shift from reactive requests to proactive analytics. * People\-first leader who invests in the growth, performance and wellbeing of the team. * Proactive and commercially curious; looks for important questions and opportunities rather than waiting for a request. * Pragmatic and evidence\-led; balances analytical rigour with pace, capacity and business need. * Direct and fair; gives clear feedback, handles difficult conversations and makes trade\-offs visible. * Calm and dependable under pressure, providing structure and direction when priorities are ambiguous or changing. * Collaborative across functions and willing to challenge constructively when the evidence requires it. * EAP support (counselling, financial and legal for you and anyone financially dependent on you). * Competitive, industry\-benchmarked salaries. * Non\-guaranteed performance bonuses. * Access to company shares (T's \& C's apply). * Wellness days. * Social clubs. * On\-site barista. Work Location: Cape Town, WC, South Africa Availability: Full time