Data Scientist

Job Title: Data Scientist Company: Setu Job Category: Data Science Roles & Responsibilities: About the Role Our Data Science team is working on understanding the financial behaviour of 1.4 billion Indians across a broad spectrum of fintech sectors—including personal lending, collections, personal finance management (PFM), and BBPS. * Translate business problems into data science and machine learning solutions. * Explore large, complex, and messy datasets to identify meaningful patterns and insights. * Build, validate, and iterate on machine learning models. * Develop scalable data pipelines and features using Python/PySpark. * Work on model deployment and contribute to production-grade ML systems. * Collaborate with product, engineering, and business teams to take models from ideation to production. * Experiment with new approaches and techniques across different data science domains. * Measure model performance and continuously improve solutions based on business outcomes. Responsibilities * Is passionate about Setu's mission and vision. * Demonstrates strong ownership, dedication, and perseverance. * Consistently creates value for customers and stakeholders through high-quality outcomes. * Strives for excellence in all aspects of their work. * Manages time effectively, prioritizes tasks, and delivers against high standards. * Adapts quickly to new responsibilities and changing circumstances. * Can independently take a problem from business understanding through modelling, experimentation, deployment, and monitoring. To excel in this role, you should have: * Take the Shot: You decide fast and deliver right. * Sign Your Work Like an Artist: You master what you do and take pride in it. * Be the Sherpa: You lead your crew on every expedition. * Be the CEO of What You Do: You own it and make things happen. * Care with Tough Love: You empower others with trust, respect, and openness. * Own Tomorrow: You innovate for the customer and beyond. Work Location: Bengaluru, Karnataka, India Availability: Full time

Experience: 0-2 years We are constantly pushing the boundaries of data science to drive business growth, improve customer experiences, and streamline operational processes. * A Bachelor's or Master's degree in Engineering or an equivalent discipline. * 0-2 years of experience in Data Science / Machine Learning. * Prior experience with one or more of the following: * BBPS data exploration * Alternate data credit risk models * Bank statement / financial transaction data * Alternate data for lenders or NBFCs * Relevant fintech or financial services use cases * Strong understanding of: * Statistics * Hypothesis testing * Statistical inference * Simulations * Optimization * Machine learning techniques * Tree-based algorithms such as Random Forest and XGBoost * Algorithms such as MLP and SVM * Experience independently converting business problems into ML models and taking them through their lifecycle. * Experience with financial sector modelling, preferably in a startup or fast-paced environment. * Experience working with unstructured, noisy, or messy data. * Hands-on experience deploying models to production, or strong experience through relevant self-driven projects. * Strong Python programming skills. * Experience building data pipelines using Python and/or PySpark. * Strong experience with feature engineering. * Proficiency in: * Pandas * Scikit-learn * SQL * Familiarity with TensorFlow and/or PyTorch. * Understanding of DevOps/MLOps practices. * Experience creating Docker containers and deploying models to production. * Experience with platforms such as Amazon SageMaker or Kubernetes. * Experience with deep learning techniques. * Exposure to LoRA fine-tuning and Generative AI. Key Skills: Data Science, Python, SQL, Pandas, Statistics, Machine Learning, Scikit-learn Salary: Not disclosed