Key Responsibilities

• Build, validate, and maintain machine learning models for forecasting, classification, regression, anomaly detection, and business analytics.
• Perform data cleaning, feature engineering, model evaluation, and performance monitoring to ensure reliable and scalable solutions.
• Develop data pipelines, automation workflows, and analytical solutions using Python and SQL.
• Analyze business data to identify trends, risks, opportunities, and key performance drivers, translating findings into actionable recommendations.
• Collaborate with business, operations, finance, and technology teams to understand requirements and deliver measurable analytical outcomes.
• Communicate model assumptions, limitations, and results effectively to both technical and non-technical stakeholders.
• Own data science projects end-to-end, including requirement gathering, development, deployment, and stakeholder management.
• Mento...