Data Science Manager

Role description

Data Science Manager

Key Responsibilities:

• 
  

  Lead a team of data scientists on end-to-end projects across one or more of the following areas:

  
  

  • Time Series Forecasting

  
  

  • Recommendation Engines

  
  

  • Causal Inference / Uplift Modeling / A/B Testing

  
  

  • Generative AI

  
  
  
  


• 
  

  Translate complex business problems into actionable data science projects.



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  Drive project scoping, solution design, development, deployment, and stakeholder communication.



• 
  

  Write clean, modular, and scalable Python code to build, validate, and deploy ML models.



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  Oversee model performance evaluation, tuning, and production monitoring.




• MLflow



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  Collaborate cross-functionally with product, engineering, and business stakeholders.



• 
  

  Stay updated on advancements in ML, GenAI, and applied analytics, and bring innovation into project design.

Required Qualifications:

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  8–12 years of experience in data science with at least 2+ years in a leadership role




• Python




• one

  
  
  • 
    

    Forecasting (ARIMA, Prophet, LSTM, etc.)

  
  
  • 
    

    Recommendation systems (collaborative filtering, content-based)

  
  
  • 
    

    Causal modeling (difference-in-differences, propensity scores, uplift models)

  
  
  • 
    

    GenAI (OpenAI APIs, LangChain, LLMs, vector databases)

  
  
  
  


• 
  

  Strong knowledge of model evaluation metrics, feature engineering, and data wrangling



• 
  

  Solid understanding of statistics, machine learning, and applied modeling

Preferred Skills:

• AWS, Azure, GCP



• 
  

  Exposure to MLOps tools (Docker, MLflow, Git, Airflow)



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  Experience deploying models via REST APIs or integrating with applications



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  Familiarity with business domains like Retail, BFSI, CPG, or Healthcare is a plus

Soft Skills:

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  Strong stakeholder management and communication abilities



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  Ability to mentor and coach team members



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  Comfortable managing multiple projects in a fast-paced environment



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  Structured problem-solving and storytelling with data