Data Science Lead

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About the Role

We are looking for a highly experienced Data Science Lead who can drive complex ML/AI initiatives, lead project delivery teams, and architect enterprise-level solutions across predictive analytics, deep learning, and production ML systems. This role requires a blend of hands-on expertise, leadership, and strategic vision.

Key Responsibilities

Leadership & Strategy

• Lead a team of data scientists, ML engineers, and analysts.
• Define data science project roadmaps, solution architecture, and delivery strategies.
• Collaborate with product, engineering, and CXO teams to translate business problems into ML solutions.

Technical Responsibilities

• Build predictive models, advanced ML pipelines, and AI-driven applications.
• Work with Python/R (NumPy, pandas, scikit-learn, TensorFlow, PyTorch).
• Apply statistical modeling, ML, deep learning, NLP, or time series forecasting.
• Architect data pipelines using Airflow, Spark, and enterprise datasets.
• Deploy models on AWS SageMaker, Azure ML, or Google AI Platform.
• Build dashboards using Power BI/Tableau or visualization libraries.

MLOps & Deployment

• Implement CI/CD for ML models.
• Manage monitoring, drift detection, retraining pipelines, and production lifecycle.

Stakeholder Collaboration

• Present insights and recommendations to business teams.
• Lead technical reviews, brainstorming sessions, and solution workshops.

Required Skills

• 10+ years of hands-on Data Science experience.
• Strong ML & statistical modeling expertise.
• Python or R proficiency.
• Strong SQL + Airflow/Spark experience.
• Hands-on with AWS SageMaker, Azure ML, or GCP AI.
• Excellent leadership, communication, and decision-making skills.

Good to Have

• Deep Learning, NLP, Time Series
• MLOps, CI/CD pipelines
• RAG, Prompt Engineering, Agentic AI
• ML certifications