Level

M&G

Senior Manager - Data Scientist (AMVC)

M&G is hiring a Senior Manager - Data Scientist (AMVC) in Pune, India. Level rates it ; you can apply on M&G.

Level's read on this job

  • Builds AI ●●●● is how Level rates this data scientist role: the job is building AI systems.
  • Tools and skills the posting cites include Copilot, PyTorch and scikit-learn.
  • Level classifies it as a senior role.
  • Level lists 86 other open roles at M&G.
  • The role was posted in the last few days.

AI in this role

Develop predictive models, machine learning systems, and apply MLOps practices to drive data science transformation initiatives.

copilotpytorchscikit-learndatabrickspythonsqlpyspark
ml-opsmachine-learningpredictive-modelingmlopsfeature-engineering

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.


  • 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
     
  • Experience:

  • 7 to 10 years of relevant work experience
     
  • Educational Qualification:

  • A numerical based degree or Post Graduate qualification

We have a diverse workforce and an inclusive culture at M&G Global Services, regardless of gender, ethnicity, age, sexual orientation, nationality, disability or long term condition, we are looking to attract, promote and retain exceptional people. We also welcome those who take part in military service and those returning from career breaks.

How we rate this

Senior Manager - Data Scientist (AMVC) at M&G rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsMachine learningPredictive ModelingMLOpsFeature EngineeringCopilotPyTorchscikit-learn

Also common in data scientist jobs at this level

Pay

Typical data scientist job
$167k

This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. Tell me about a project where machine learning was part of your work. What did you do?
  3. Tell me about a project where predictive modeling was part of your work. What did you do?
  4. Tell me about a project where mlops was part of your work. What did you do?
  5. Tell me about a project where feature engineering was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: ML Ops, Machine learning, Predictive Modeling, MLOps, and Feature Engineering. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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