Senior Data Scientist - Machine Learning

Job description

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: 1. Demand Forecasting 2. Price Optimization 3. Inventory Optimization / Supply Chain Analytics 4. Causal Inference 5. Recommendation • 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.