Company Profile:

Prevalent AI (PAI) is a Security Data Science Company, founded in the UK, by experts recognized globally, for solving the world’s toughest security problems. We apply the world’s best Security Data Science knowledge and expertise to help companies understand, deploy and support the most advanced security solutions, by developing a security architecture based on a deep understanding of Data Science, Security Tradecraft and Big Data Technologies.

PAI’s Security Data Science Platform (SDS) is a big data security analytics platform that can ingest wide range of security telemetry data and apply advanced analytical approaches to identify and detect control weakness and security risks within enterprises. Prevalent AI India Pvt Ltd., a subsidiary of Prevalent AI, has offices in Infopark, Cochin, Kerala. For more information, please visit https://www.prevalent.ai

Role Purpose and Key Accountabilities:

We are looking for seasoned Security Analysts for our Client Delivery and Solution Development teams, with proven experience in - analysing large volumes of complex raw data, creating business value out of it to develop analytical products, by analysing and investigating security risks and incidents and leveraging security technologies.

This role is highly collaborative and will interact effectively with various internal stakeholders. It is essential to have a broad understanding of various relevant technologies, with deep expertise to be hands-on with some of them. The ideal candidate would also be a self-starter and self-motivated individual with a strong commitment to quality, a positive work ethic, and a "can do" attitude.

The role of a Lead Security Analyst has a few key dimensions:

Solution design and development : Develop PAI’s Security Data Science Platform (SDS) and analytics solutions by working with other stakeholders to develop and extend security analytics models for identifying and detecting security risks using a range of industry frameworks like NIST, CIS, ISO27001. This involves:

· Ideation of features/analytical outputs

· UX design and prototyping

· Use case / Outcome documentation

Data Analysis : Data Source Analysis & Source System Analysis

· Identifying data sources for solution implementation. e.g.: identifying Splunk indexes, API endpoints.

· Understanding of the Source System and the other competing vendor solutions in this space.

· API Documentation - Authentication, Data Volume, Output data, Ingestion Methodology.

· Exploratory analysis of data (EDA) required to support use cases.

· Identifying patterns, relationship/co-relation with data sources and perform volumetric analysis.

Stakeholder /Client Engagement : Work with experienced client security teams to analyze and investigate security risks and controls, to help enterprises improve their security risk posture. This would involve:

· translating client/solution requirements to security use-cases.

· designing analytics to support use-cases.

· translating use-cases to solutions features.

· explaining Why and How a feature will reduce a security risk.

· using and demoing our solutions using client data.

· presenting insights confidently and positioning them well for the target audience.

Market Research : Understanding of various security architecture, security tools and processes widely used in an Enterprise; as well as various security user personas, their roles and responsibilities and their pain points, to help understand how the PAI solution landscape addresses these pain points.

Data Modelling : Supporting development of security analytics based on source system analysis in addition to designing and building entities and relationships.

Testing : Functional Validation of analytics developed.

Documentation & Training : Responsibility for various documentation artefacts like Use case, Functional Design, User Guide, Developer Guide documentation.

Skills and Experience:

· Significant experience in analysing security risks using a range of security tools and products.

· Hands-on experience in data modelling, data warehousing, conceptual, logical and physical model development in relational database environments.

· Experience conducting information security risk assessments based on industry risk frameworks to identify and evaluate mitigating controls.

· Excellent attention to detail, analytical skills and problem solving skills with an ability to analyse complex technical information in order to identify patterns and trends.

· Experience using SIEM tools like Splunk.

· Self-motivated individual capable of working in a fast-paced environment.

· Great written and verbal communication skills, including presentation skills, with an ability to communicate with a range of technical and non-technical team members and other relevant individuals.

· Excellent consultative, facilitative, and consensus-building abilities

Knowledge:

· Exposure to multiple information security and cyber security frame works like NIST CSF, CIS OWASP 10, MITRE, ISO 27001.

· Breadth and depth of security knowledge in multiple domains of software network & cloud security, based on working experience within information security teams and security operations.

· Understanding of the cyber security risks, attacks and threats associated with various technologies and ways to manage them.

· Ability to query in Data Lake for conducting detailed analysis using Pyspark, SQL, etc and familiarity with industry-standard data modelling methodologies.