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M&G plc.
Mumbai, INDIA
(on-site)
Job Function
Financial
Manager - Data Scientist (AMVC)
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Manager - Data Scientist (AMVC)
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Description
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.
Responsibilities:
- Strong knowledge in predictive modelling and machine learning, including supervised and unsupervised techniques (e.g. regression, classification, clustering, anomaly detection)
- Ability to support translating business problems into data science solutions, with guidance from senior team members
- Experience to model development, validation and tuning, with an understanding of model robustness and interpretability concepts.
- 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).
- Good communication skills, with the ability to explain analysis and results clearly with support as needed.
- Willingness to learn from feedback and collaborate with team members on reviews and deliverables
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
- Ability to interpret financial methodology and reporting results
- Process reengineering, control design and audit-ready documentation
- Responsible use of AI design and coding assistants (GitHub Copilot, Copilot 365)
- Experience in financial services / insurance / actuarial analytics environments
- 2 to 6 years of relevant work experience
- A numerical based degree or Post Graduate qualification
Job ID: 84373616
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