Data Scientist - Analytics & AI/ML

About team

The Data Value function is based in India and supports Fidelity Internationals Sales, Marketing, Propositions, Risk, Finance, Customer Service and HR teams across the globe. The key objectives of the function are:

• To develop deep customer insights for our businesses helping them segment and target customers more effectively
• To develop a fact based understanding of sales trends and identify actionable sales growth opportunities for each of our sales channels
• To understand customer preferences in terms of products, service attributes and marketing activity to help refine each of these
• To help develop new services lines e.g. develop customer analytics for key IFAs, DC Clients, Individual clients etc.
• To develop market and competitive intelligence in our key markets to help shape our business planning in those markets
• The function works directly with business heads and other senior stakeholers to identify areas of analytics, define problem statements and develop key insights.

About your role

• As an experienced contributor, you will use data, statistical techniques and business understanding to solve problems and support decision-making.
• This is a broad analytics role requiring strong data science foundations.
• Your work will include exploratory analysis, segmentation, predictive modelling, hypothesis testing, automation and business insight generation.
• You will work within a cross-functional pod alongside senior analysts, data scientists, data engineers, Power BI developers and business stakeholders. You will be expected to select the analytical approach most appropriate to the business problem rather than applying machine learning in every situation.
• Translate business questions into clear hypotheses and analytical approaches
• Analyse customer, commercial and operational data to identify trends, opportunities, risks and performance drivers.
• Lead end-to-end development of statistical, machine-learning and AI solutions to complex business problems
• Apply techniques such as segmentation, propensity modelling, forecasting, customer behaviour modelling and next-best-action.

Experience & Qualifications

• Bachelors or Masters degree in a quantitative, analytical or business discipline, or equivalent relevant professional experience.
• 5-9 years of relevant experience across Data Science, advanced analytics, customer analytics or broader business analytics, with increasing ownership of complex analytical problems.
• Strong hands-on Python and SQL skills, with the ability to independently analyse, manipulate and interrogate large and complex datasets.
• Strong grounding in statistics and machine learning, including hypothesis testing, segmentation, regression/classification, forecasting, predictive modelling and model evaluation.
• Experience across the end-to-end Data Science lifecycle, including exploratory analysis, feature engineering, model development, validation, interpretation and performance assessment
• Experience working with modern cloud and data platforms, preferably Snowflake and AWS, and an understanding of scalable analytical data structures and pipelines.
• Exposure to Generative AI and modern AI techniques, alongside a sound understanding of data quality, explainability, governance and responsible use of analytical models.