Data Science Manager

Role description

We are looking for an experienced and hands-on Data Science Manager who can lead and deliver high-impact projects across domains such as Forecasting, Recommendation Systems, Causal Inference, and Generative AI (GenAI). The ideal candidate will combine strong Python coding abilities with leadership and solutioning skills to manage a team and work closely with business and engineering stakeholders.

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

  
  
  
  
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    Time Series Forecasting (demand, sales, financial)

    
    
  
  
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    Recommendation Engines (content, product, personalization)

    
    
  
  
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    Causal Inference / Uplift Modeling / A/B Testing

    
    
  
  
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    Generative AI (summarization, copilots, semantic search using LLMs)

    
    
  
  
  
  


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  Translate complex business problems into actionable data science projects.

  
  


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

  
  


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  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.

  
  


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  Guide the team in adopting modern tools: MLflow, LangChain, XGBoost, Prophet, Vector DBs, etc.

  
  


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

  
  


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

  
  

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

  
  


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  Strong hands-on experience in Python (Pandas, NumPy, Scikit-learn, Statsmodels, Matplotlib, etc.)

  
  


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  Proven project experience in at least one of the following:

  
  
  
  
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    Forecasting (ARIMA, Prophet, LSTM, etc.)

    
    
  
  
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    Recommendation systems (collaborative filtering, content-based)

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

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

    
    
  
  
  
  


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

  
  


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  Solid understanding of statistics, machine learning, and applied modeling

  
  

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  Experience with cloud platforms (AWS, Azure, GCP)

  
  


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  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

  
  

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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