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 Quantiums 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.

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
- 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
- Experience and Qualifications
- 4-6 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
- Skills and Competencies
- Technical
- Sound knowledge of analytics methodology: data preparation, experiment design, feature engineering, model development, training, and evaluation
- Specialisation depth expected sufficient skill in several analytics disciplines to work autonomously, and authoritative expertise in at least one area to guide others and solve high complexity problems
- Strong proficiency in Python and SQL; comfort with up-to-date development practices including version control, code review, and CI/CD concepts
- Growing familiarity with AI/GenAI tooling: AI-assisted coding, prompt engineering, LLM integration, and automated validation approaches
- Ability to follow and advocate for analytics best practices as defined at Quantium, suggesting improvements where appropriate

📌 Senior Data Scientist (Hyderabad)
🏢 Quantium Analytics
📍 Hyderabad