Senior Manager - Data Scientist (AMVC)

Requirements

• 7 to 10 years of relevant work experience
• Educational Qualification:
• A numerical based degree or Post Graduate qualification

Additional Information

We are M&G Global Services Private Limited (formerly known as 10FA India Private Limited, and prior to that Prudential Global Services Private Limited). We are a fully owned subsidiary of the M&G group of companies, operating as a Global Capability Centre providing a range of value adding services to the Group since 2003. Our purpose is to give everyone real confidence to put their money to work. With a heritage dating back more than 175 years, we have a long history of innovation in savings and investments, combining asset management and insurance expertise to offer a wide range of solutions. Our two distinct operating segments, Asset Management and Life, work together to provide access to balanced, long-term investment and savings solutions. M&G Global Services has rapidly transformed itself into a powerhouse of capability that is playing an important role in M&G's ambition to be the best loved and most successful savings and investments company in the world. Our diversified service offerings extending from Digital Services (Digital Engineering, AI, Advanced Analytics, RPA, and BI & Insights), Business Transformation, Management Consulting & Strategy, Finance, Actuarial, Quants, Research, Information Technology, Customer Service, Risk & Compliance and Audit provide our people with exciting career growth opportunities. Through our behaviours of telling it like it is, owning it now, and moving it forward together with care and integrity; we are creating an exceptional place to work for exceptional talent. Primary Key Responsibilities (Top 3-5 KRA) Strong experience in predictive modelling and machine learning, including supervised and unsupervised techniques (e.g. regression, classification, clustering, anomaly detection) Proven ability to translate business problems into data science solutions and deliver measurable outcomes Hands-on expertise in model development, validation, tuning and interpretability, ensuring robustness and explainability. Experience working with large, complex datasets and performing feature engineering and data preparation. Proficiency in Python for data science and machine learning applications. Working knowledge of SQL and data manipulation for extracting and preparing datasets. Working knowledge with PySpark / Databricks or similar distributed data environments. Understanding of financial data, actuarial processes or reporting frameworks (preferred but not mandatory). Strong communication and stakeholder management skills, with the ability to clearly explain model outputs, assumptions and limitations. Experience reviewing work and guiding junior team members. Knowledge & Skills (Must Have) : Predictive modelling and machine learning (model selection, evaluation, validation, interpretability) Exposure to MLOps concepts (model deployment, monitoring, lifecycle management) Applied Python, SQL and Databricks (PySpark, Delta, jobs/workflows) skills GitHub and DevOps for source control, code review and CI/CD Python for data science (e.g. pandas, scikit-learn, PyTorch, statistical modelling) Statistical and analytical thinking applied to real-world problem solving. Data preparation, feature engineering and handling structured/unstructured datasets. Ability to link model outputs to business decisions and insights. Clear documentation of models, assumptions and results in an audit-aware environment Knowledge & Skills (Additional) : Ability to interpret financial methodology and reporting results Process reengineering, control design and audit-ready documentation Coaching and technical review of junior colleagues Responsible use of AI design and coding assistants (GitHub Copilot, Copilot 365) Experience in financial services / insurance / actuarial analytics environments

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