Data Scientist (Senior)

Quantium

Since 2002, Quantium have combined the best of human and artificial intelligence to power possibilities for individuals, organisations and society. Our solutions make sense of what has happened and what will, could or should be done to re-shape industries and societies around the needs of the people they serve.

As one of the world's fully diversified data science and AI leaders we operate across every sector of the economy and we're growing fast - with growth comes opportunity! We're passionate about building out our team of smart, fun, diverse and motivated people.

We combine a team of experts that spans data scientists, actuaries, statisticians, business analysts, strategy consultants, engineers, technologists, programmers, product developers, and futurists – all dedicated to harnessing the power of data to drive transformational outcomes for our clients.

We actively foster a culture where our people can stretch themselves to reach their full potential. We also know that work has to work for you, and modern life is fast-paced, and balance can be tricky. You want to work where you are respected and valued as an individual, not a number. Quantium embraces a flexible and supportive environment dedicated to powering possibilities for our team members, clients and partners.

Based in Hyderabad, Quantium India provides vital support to the global business. The teams in India work alongside global teams to deliver high quality analytics solutions to clients.

Role Summary

The Senior Data Scientist, Product Analytics is a hands-on technical contributor and task manager within a cross-functional product team. Working closely with the Analytics Lead, Delivery Managers, and specialists from analytics and engineering disciplines, you will be responsible for designing, building, and deploying analytics solutions that form the core of Quantium’s software products.
This role sits at the intersection of deep technical execution and emerging AI capability. You are expected to deliver high-quality analytical work autonomously, manage task allocation across junior team members, and increasingly leverage AI tools and techniques to accelerate and improve your work. You bring both rigour in established methods and curiosity about what AI-augmented analytics can achieve.

Experience and Qualifications

•5–7 years of experience in a highly technical analytics or data science environment
•Demonstrated experience delivering analytics solutions within a product or platform context, working in cross-functional teams
•Experience with task management or technical oversight of junior team members
•Exposure to AI/ML techniques in a practical setting; hands-on experience with generative AI tools is a strong plus
•Tertiary qualifications in engineering, mathematics, statistics, computer science, physics, or a related quantitative discipline

Key Responsibilities

Analytics Delivery
•Accountable for delivering advanced analytics solutions into Quantium products on time and at the required level of quality
•Lead assigned sections of analytics solution design with minimal guidance — typically components with clear input/output requirements such as predictive models, allocation schemes, or data transformation pipelines
•Design, develop, prototype, and test analytics algorithms, writing clear specifications for implementation by engineering teams where required
•Carry out BAU production processes for product components that require regular delivery, ensuring reliability and accuracy
•Investigate and resolve data quality issues, user objections, or anomalies raised during product operation

AI-Augmented Analytics
•Actively adopt AI tools and techniques to improve personal and team productivity — including AI-assisted coding, automated data validation, and GenAI-driven analysis workflows
•Contribute to the development and testing of AI-powered product features, such as natural language interfaces, intelligent data exploration, or automated reporting
•Prototype and evaluate new AI/ML approaches for solving analytical problems, working with the Analytics Lead to assess feasibility and production-readiness
•Build familiarity with prompt engineering, LLM integration patterns, and retrieval-augmented generation as these become part of the product toolkit

Task Management and Peer Development
•Oversee and delegate technical tasks to analysts and graduates, ensuring work is distributed effectively and delivered to standard
•Peer review the work of other analysts — both methodology and code — to ensure correct implementation and adherence to Quantium’s analytics best practices
•Follow and instil best practice guidelines, tools, and formal processes for analytics within the team
•Actively drive improvement in the capability and quality of work of junior team members through coaching and knowledge sharing

Client and Stakeholder Liaison
•Act as a key client liaison, translating business requirements into modelling specifications for assigned analytics workstreams
•Liaise with internal and external product stakeholders to respond to queries, communicate delivery updates, and manage expectations
•Provide estimates of work effort, timeframes, and costings for analytics tasks, and peer review estimates from team members

Continuous Improvement
•Create analytics approaches that solve business problems in a scalable and repeatable way
•Suggest improvements to existing analytics processes, tools, and workflows — including identifying automation opportunities
•Participate in Quantium’s Analytics Community through peer reviews, knowledge-sharing sessions, and collaborative problem-solving
•Take active steps to drive own career development and deepen technical expertise, seeking guidance as needed

Key Activities

•Delivering analytics components within cross-functional product teams managed by a Product Lead or Delivery Manager
•Designing and building data pipelines, models, and validation frameworks that operate reliably at scale
•Writing specifications for analytics algorithms to be implemented by software engineers
•Supporting product migration and transition work, picking up operational knowledge and building India team capability
•Applying AI tools to accelerate routine analytical tasks — data profiling, code generation, documentation, and testing
•Conducting exploratory analysis and discovery work to identify new use cases and product improvement opportunities
•Producing clear documentation of methodology, assumptions, and limitations for all analytical work