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M&G

Publicly traded savings and investments company

Data Scientist

Data EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Strong expertise in data science techniques, including machine learning and their application in financial services.
  • Proficiency in data tools, programming languages, and database technologies, particularly Azure Databricks, Spark, Spark SQL, Python, and PySpark.
  • Understanding of data governance, security, and data quality management principles.
  • Experience working with large, complex datasets and performing feature engineering and data preparation.
  • Ability to translate business problems into data science solutions and deliver measurable outcomes.
  • Experience working in Financial Services or a similarly heavily audited environment, with an understanding of operating controls and producing audit evidence.
  • Knowledge of data pipeline development and optimisation.
  • Knowledge of data modelling and architecture in Azure Databricks.
  • Knowledge of programming and scripting for data processing using Spark, Spark SQL, Python, and PySpark.
  • Knowledge of data science and machine learning.
  • Knowledge of data governance and quality assurance.
  • Ability to engage stakeholders and communicate technical information, including at design forums where relevant.
  • Ability to guide others and contribute to continuous improvement and innovation.
  • Knowledge of performance tuning and optimisation.
  • People management skills.

Responsibilities

  • Design, build, and maintain scalable data pipelines to validate and transform data to meet actuarial modelling needs.
  • Ensure data quality, integrity, and consistency through robust validation, monitoring, and governance practices.
  • Collaborate with stakeholders to understand data requirements and translate them into efficient and effective technical solutions.
  • Optimise data systems and processes to improve performance, reliability, and scalability.
  • Provide technical expertise and guidance on data science approaches, tools, and best practices.
  • Support integration of multiple data sources to create cohesive, accessible, and trusted datasets.
  • Contribute to the continuous improvement of data platforms, frameworks, and engineering standards.
  • Lead the design and build of data workflows, drive process reengineering and transformation, and embed controls required for audit and risk assurance.
  • Apply machine learning and advanced analytics where they add measurable value.
  • Guide and develop junior team members by reviewing their analysis and code, providing technical advice, and coaching them on controls and documentation.
  • Maintain high standards for documentation and development, proactively identifying inefficiencies in existing processes.
  • Communicate findings clearly and in a structured manner.

About the Company

M&G

Publicly traded savings and investments company

M&G is a savings and investments company that manages money for individuals and institutions. It offers a range of investment products, including mutual funds, where many investors pool their money to buy a fixed mix of assets chosen by the fund manager. The funds are then managed to try to grow wealth and provide long-term returns, with investors’ money divided into shares or units based on the fund’s rules. M&G differentiates itself through its long history as an asset manager, its status as an independently listed company after the demerger from Prudential, and its focus on serving the UK and European markets with a broad lineup of funds and investment strategies. Its goal is to help people save and invest for the long term by providing access to professionally managed portfolios and investment options that suit different risk tolerances and goals.

Company size
1,001-5,000
Company stage
IPO
Headquarters
London, United Kingdom
Founded
1931

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