Senior Data Scientist

Location: Hyderabad, India

About the Role
We're looking for a Data Scientist with strong breadth across classical data science and hands-on depth in forecasting. The ideal candidate can work across the full data science lifecycle - from problem framing and data exploration to modeling and deployment - and brings specific, demonstrable experience with time-series and demand forecasting problems.

Key Responsibilities

• Work across the full data science lifecycle - problem framing, EDA, feature engineering, modeling, validation, and deployment

• Build and maintain forecasting models (time-series and demand/sales forecasting) for client and internal use cases

• Apply classical ML techniques - regression, classification, and clustering - to a range of business problems

• Perform rigorous EDA and data quality checks to ensure reliable, production-ready datasets

• Collaborate with clients and internal stakeholders to translate business problems into data science solutions

• Communicate findings and model outputs clearly to both technical and non-technical audiences

• Support deployment and monitoring of models in production environments

• Mentor junior data scientists as needed

Required Skills & Experience

• 4-6 years of experience in data science/analytics roles with a broad, generalist skill set

• Strong, hands-on experience with forecasting - time-series methods (ARIMA, Prophet, exponential smoothing) and/or ML-based forecasting approaches

• Solid grounding in classical ML - regression, classification, clustering, and feature engineering

• Proficiency in Python and standard data science libraries (pandas, scikit-learn, statsmodels)

• Experience with SQL and working with large, real-world datasets

• Experience deploying or operationalizing models, not just notebook-level analysis

• Strong communication skills - comfortable presenting findings to clients and stakeholders

• Ability to work independently and manage ambiguous, client-facing problems

Good to Have

• Experience with cloud platforms (AWS/Azure/GCP)

• Exposure to MLOps tooling and practices

• Experience working directly with external clients

• Awareness of and interest in the latest Gen AI and agentic AI technology, and how it applies to data science workflows

• Exposure to optimization modeling (e.g., linear/mixed-integer programming, heuristics)