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About the Opportunity Job TypeApplication 20 June 2025 Title Data Scientist, Risk Data Analytics Department Data Value Location Gurgaon Reports To Associate Director, Risk Data Analytics Level 5 Were proud to have been helping our clients build better financial futures for over 50 years. How have we achieved thisBy working together - and supporting each other - all over the world. So, join our Data Value team and feel like youre part of something bigger. About Global Risk The Global Risk team in Fidelity covers the management oversight of Fidelitys risk profile, including key risk frameworks, policies and procedures and oversight and challenge processes. The team partner with the businesses to ensure Fidelity manages its risk profile within defined risk appetite. The team comprises risk specialists covering all facets of risk management, including investment, financial, non-financial and strategic risk. As part of a broader General Counsel team, the Risk team collaborates closely with Compliance, Legal, Tax and Corporate Sustainability colleagues. About Risk Data Analytics Hub The vision of Risk Data Analytics Hub is to establish a data-centric risk function that is forward-thinking, resilient, and proactive. The hubs mission is to enhance risk management processes and unlock innovative opportunities in the ever-changing risk and business landscape. The Hub has made significant strides in the Investment Risk, delivering prominent contributions such as the Fund Performance Monitoring, Fund Aggregate Exposures, Fund Market Risk, Fund Liquidity Risk, and other comprehensive monitoring and reporting dashboards. These tools have been crucial in supporting risk oversight and regulatory submissions. The Hubs goal is to scale this capability across global risk, using data-driven insights to uncover hidden patterns and predict emerging risks. This will enable decision-makers to prioritise actions that align with business objectives. The approach is to dismantle silos and foster collaboration across the global risk team, introducing new tools, techniques, and innovation themes to enhance agility. About your role You will be expected to take a leading role in developing the Data Science and Advanced Analytics solutions for our business. This will involve: Engaging with the key stakeholders to understand various subject areas in Global Risk Team including Investment Risk, Non-Financial Risk, Enterprise Risk, Model Risk, Enterprise Resilience etc. Implement advanced analytics solutions on On-Premises/Cloud platforms, develop proof-of-concepts and engage with internal and external ecosystem to progress the proof of concepts to production. Engaging and collaborating with different other internal teams like Data Lake, Data Engineering, DevOps/MLOps, Technology team etc for development of new tools, capabilities, and solutions. Maximize adoption of Cloud Based advanced analytics solutionsBuild out sandbox analytics environments using Snowflake, AWS, Adobe, Salesforce. Support delivered models and infrastructure on AWS including data changes and model tuning About you Key Responsibilities Developing and Delivering Data Science solutions for business (40%) Partner with internal (FIL teams) & external ecosystem to design and deliver advanced analytics enabled Data Science solutions. Create advanced analytics solution on quantitative and text data using Artificial Intelligence, Machine Learning and NLP techniques. Create compelling visualisations that enable the smooth consumption of predictions and insights for customer benefit. . Stakeholder Management (30%) Works with Risk SMEs/Managers, stakeholders and sponsors to understand the business problem and translate it into appropriate analytics solution. Engages with key stakeholders for smooth execution, delivery, implementation and maintenance of solutions. Adoption of Cloud enabled Data Science solutions(20%) Maximize Adoption of Cloud Based advanced analytics solution Build out sandbox analytics environments using Snowflake, AWS, Adobe, Salesforce Deploy solutions in productions while adhering to best practices involving Model Explainability, MLOps, Feature Stores, Model Management, Responsible AI etc Collaboration and Ownership (10%) Sharing of knowledge, best practices with the team including coaching or training in some of deep learning/ machine learning methodologies. Provides mentoring, coaching, and consulting advice and guidance to staff, e.g. analytic methodologies, data recommendations. Takes complete independent ownership of the projects and the initiatives in the team with the minimal support. Experience and Qualifications Required Qualifications: Engineer from IIT/Masters in field related to Data Science/Economics/Mathematics (Tie1 Institutions like ISI, Delhi School of Economics)/M.B.A from tier 1 institutions Must have Skills & Experience Required: Overall, 9+ years of experience in Data Science and Analytics 5+ years of hands-on experience in - Statistical Modelling /Machine Learning Techniques/Natural Language Processing/Deep Learning 5+ years of experience in Python/Machine Learning/Deep Learning Excellent problem-solving skills Should be able to run analytics applications such as Python, SAS and interpret statistical results Implementation of models with clear measurable outcomes Good to have Skills & Experience Required: Ability to engage in discussion with senior stakeholders on defining business problems, designing analyses projects, and articulating analytical insights to stakeholders. Experience on SPARK/Hadoop/Big Data Platforms is a plus. Experience with unstructured data and big data. Experience with secondary data and knowledge of primary market research is a plus. Ability to independently own and manage the projects with minimal support. Excellent analytical skills and a strong sense for structure and logic. Ability to develop, test and validate hypotheses.
