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Project Manager-Data Scientist

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Onsite

Project Manager-Data Scientist

Reserve Bank Information Technology

Project Manager-Data Scientist

Skills

Deep LearningData ScienceData AnalysisMachine LearningAINLP / Natural Language ProcessingCompliance

2 months ago

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Important information


Contract type:

Permanent

Location:

Navi Mumbai, Maharashtra, India

Work mode:

Onsite

Published on:

13 August 2026

What they need


Job Summary

We are seeking an experienced Data Science Project Manager to lead end-to-end delivery of data science, machine learning, and advanced analytics projects. The ideal candidate will bridge the gap between business stakeholders and technical teams, ensuring timely, high-quality delivery of data-driven solutions aligned with business objectives.

Key Responsibilities

Project & Delivery Management

  • Lead end-to-end delivery of Data Science, Machine Learning, AI, and Analytics projects.
  • Define project scope, timelines, milestones, dependencies, and resource plans.
  • Manage project execution using Agile/Scrum or Hybrid methodologies.
  • Track project progress, risks, issues, and dependencies; implement mitigation plans.
  • Ensure on-time, within-scope, and within-budget delivery.

Technical & Data Science Oversight

  • Work closely with Data Scientists, Data Engineers, and ML Engineers on:

  • Data ingestion, cleaning, and feature engineering

  • Model development, validation, and deployment

  • ML lifecycle management (MLOps)

  • Review and validate technical designs, model approaches, and solution architectures.

  • Understand algorithms such as regression, classification, clustering, NLP, time series, and deep learning.

  • Ensure model performance, scalability, explainability, and compliance standards.

Stakeholder & Client Management

  • Act as the primary point of contact for business stakeholders and clients.
  • Translate business requirements into technical deliverables and project plans.
  • Present project updates, insights, and results to senior leadership.
  • Manage client expectations, change requests, and escalations effectively.

Governance, Quality & Compliance

  • Ensure adherence to data governance, security, and compliance standards.
  • Drive documentation for requirements, design, models, and delivery artifacts.

Ensure quality checks, validation, and sign-offs at each project phase

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