Senior Data Scientist

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: 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.