Senior Data Scientist - Classical Machine Learning

We are looking for a Senior Data Scientist who is passionate about solving complex business problems using data. The ideal candidate will have strong hands-on experience in Python, SQL, and advanced machine learning algorithms, along with domain expertise in forecasting, pricing optimization, or inventory planning. You will work closely with cross-functional teams including product, engineering, and business stakeholders to drive data-driven strategies.

Key Responsibilities:

• Design, build, and deploy predictive and optimization models for use cases such as demand forecasting, dynamic pricing, or inventory optimization.
• Translate business problems into analytical frameworks and provide actionable insights.
• Build and maintain scalable data pipelines and model workflows using Python and SQL.
• Collaborate with data engineers to ensure model integration into production systems.
• Present findings and recommendations to leadership using data visualizations and storytelling.
• Stay current with the latest techniques in machine learning, statistics, and operations research.
• Lead and mentor junior data scientists and analysts when required.

Required Skills and Experience:

• 5+ years of experience in a Data Science or Analytics role with a strong business impact.

• Strong programming skills in Python (pandas, scikit-learn, statsmodels, etc.).

• Proficiency in SQL for data extraction, transformation, and manipulation.

• Deep understanding of machine learning algorithms (regression, classification, clustering, time series forecasting).

• Experience with one or more of the following domains:

• Demand Forecasting

• Price Optimization

• Inventory Optimization / Supply Chain Analytics

• Strong problem-solving and quantitative skills.

• Experience working with large datasets and distributed computing tools (e.g., Spark, Hadoop) is a plus.

• Familiarity with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn).

Preferred Qualifications:

• Masters or PhD in Computer Science, Statistics, Mathematics, Economics, Operations Research, or a related field.
• Experience in retail, e-commerce, manufacturing, or logistics is a strong plus.
• Exposure to optimization libraries (e.g., PuLP, OR-Tools, Gurobi) is a bonus.
• Experience deploying models using MLOps tools or platforms is a plus.