Senior Manager - Data Analyst - Methodology & Assumption (M&A) Actuarial

About M&G India We are M&G India, the strategic innovation and digital hub for M&G. Established in 2003, we have offices in Mumbai and Pune. Our teams work closely with colleagues across the Group worldwide to drive transformation, build digital capability, and support sustainable growth. By leveraging technology, AI, automation, and process excellence, we bring new ways of thinking to improve outcomes for both customers and colleagues. Grounded in a vibrant culture with strong foundations, we are central to how M&G is transforming as a business. About M&G 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. Through 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. Overall Job Purpose Individual would be part of the Methodology & Assumption (M&A) Actuarial Policyholder Data Team within the Actuarial Modelling & Valuation Centre of Excellence in Finance. A new solution for the validation and transformation of policyholder data used in actuarial modelling and assumption setting is being built. This role will operate, maintain and make BAU updates to the new data pipelines which will validate, transform and enrich data for use in actuarial modelling and assumption setting. It will use its strong data analysis skills to investigate and resolve data issues found pre-emptively or those raised by stakeholders. The role contributes to the continuous improvement of data processes, ensuring accuracy, consistency, and clarity in outputs while working within defined guidelines. Communication of findings is clear, structured, and tailored to support stakeholders in progressing with confidence. Individual is accountable and responsible for the Model Points Data Production and Experience Analysis related tasks as assigned by the Team Manager. The person would act as necessary support to the team by carrying the tasks for the process with an acceptable standard of quality and within agreed timelines. Primary Key Responsibilities Ensure data integrity by applying validation, quality checks, and governance standards. Implement controls and remediation actions to improve data accuracy and completenessMaintain process documentation, data dictionaries, and operational proceduresCollaborate with stakeholders to understand data requirements and translate them into transformation logic and code that into the pipeline. Support internal and external audit queries with timely and comprehensive responsesApply data analysis techniques to answer queries raised by users of the data. Ensure all enhancements are appropriately documented and meet business requirements before implementation. Additional Responsibilities : Produce clear and accurate reports, dashboards, and visualisations to support business decisions. Support the development and refinement of data processes, tools, and methodologies. Communicate findings in a concise, structured, and accessible way to both technical and non-technical audiences. Work independently within established frameworks, managing own and teams workload managementDeliver high-quality outputs with strong attention to detail, ensuring accuracy, consistency, and compliance with agreed standards Key Stakeholder Management Internal M&G India Team manager UK Team manager Other Senior Stakeholders Risk Team External Diligenta PwC WTW Knowledge, Skills, Experience & Educational Qualification Knowledge & Skills (Must Have) : Strong analytical capability with the ability to interpret and translate data into meaningful insights. Proficiency in data analysis tools, reporting platforms, and structured query languages. Understanding of data governance, data quality, and validation practices. Ability to communicate complex information in a clear, structured, and engaging way. Strong attention to detail and commitment to delivering accurate, high-quality work. Collaborative approach, with the ability to build effective working relationships across teams. Experience working in Financial Services or a similar heavily audited environment with an understanding of operating controls and producing audit evidenceAbility to prioritise tasks and manage workload effectively within defined processes. Stakeholder engagementProblem Solving and Root Cause AnalysisContinuous improvement mindsetExperience maintaining documentation, controls, and governance evidence to support auditability and operational resilienceExperience using Excel, Power BI, and/or Python to analyse data, automate checks, and produce reports or .