Senior Manager / Delivery Lead - Data Science

Senior Manager Data Science

technical leadership, people management, and cross-functional collaboration

Key Responsibilities

Leadership & Strategy

• Define and execute the

  data science roadmap

  aligned with business goals.
• Lead teams of Data Scientists, ML Engineers, and Analysts across multiple projects.
  
• Champion

  data-driven decision making

  and evangelize AI/ML/GenAI adoption across the organization.
• Partner with senior executives to identify high-value opportunities and shape long-term AI strategy.
  

Technical Oversight

• Provide architectural and technical direction for

  ML models, predictive analytics, GenAI solutions, NLP, LLM, and optimization models

  .
• Oversee end-to-end model life cycle: data exploration, feature engineering, modeling, evaluation, deployment, monitoring.
  
• Review and guide development of

  RAG systems, LLM pipelines, forecasting models, recommendation engines, and risk scoring systems

  depending on business needs.
• Ensure best practices in

  MLOps, versioning, reproducibility, and scalable deployment

  .

Team Management & Development

• Manage and mentor a team of 1030 data professionals depending on organizational setup.
  
• Drive talent development through coaching, performance management, and skill-building initiatives.
  
• Foster a culture of innovation, experimentation, and technical excellence.
  

Cross-Functional Collaboration

• Collaborate closely with Engineering, Product, BI, Cloud, and Business stakeholders.
  
• Translate business problems into analytical frameworks and actionable insights.
  
• Work with product and engineering teams to integrate AI solutions into production systems.
  

Governance, Quality & Delivery

• Ensure projects are delivered with high quality, accuracy, and business impact.
  
• Establish best practices for

  model governance, documentation, model risk management, and compliance

  .
• Prepare executive-level presentations, dashboards, and communication materials.
  

Required Qualifications

• Master’s or PhD in

  Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or related fields

  .

• 12–15 years of experience

  in data science, advanced analytics, or AI, including at least

  5+ years in people leadership roles

  .
• Strong technical expertise in:
  
• Machine learning, deep learning, NLP, GenAI, LLM fine-tuning
  
• Statistical modeling, forecasting, optimization
  
• Cloud platforms (AWS, Azure, GCP) and MLOps frameworks
  
• Proven experience delivering enterprise-scale AI/ML solutions.
  
• Excellent leadership, communication, and stakeholder management skills.
  

Preferred Skills

• Experience in

  GenAI/LLM platform architecture, prompt engineering, and model evaluation

  .
• Strong understanding of

  data engineering

  , data architecture, and real-time pipelines.
• Familiarity with

  AI ethics, governance, and model risk frameworks

  .
• Experience working in

  BFSI, Retail, Healthcare, Manufacturing, or Tech

  domains (customize as needed).
• Prior experience managing

  multi-location or global teams

  .