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Job Description

Role Overview :

The Senior Data Scientist, Product Analytics is a hands-on technical contributor and task manager within a cross-functional product team. This role sits at the intersection of deep technical execution and emerging AI capability.

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

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