Senior Data Science Professional

Key Responsibilities

• Translate ambiguous business problems into structured analytical and model-driven solutions aligned with business objectives
• Partner with stakeholders to define hypotheses, success metrics, and analytical approaches for decision-making
• Perform deep exploratory data analysis (EDA), hypothesis testing (A/B testing, what-if analysis), and scenario modeling
• Develop statistical, machine learning, and hybrid AI models to solve complex business problems such as churn prediction, revenue optimization, anomaly detection, and operational efficiency
• Build scalable analytical workflows and feature engineering pipelines using Python, SQL, and BigQuery
• Design and implement predictive models using classical ML and advanced analytics techniques
• Identify inefficiencies and anomalies in business systems using KPI-based monitoring and outlier detection methods
• Ensure data consistency, accuracy, and reliability through robust validation and governance frameworks
• Monitor model performance, implement feedback loops, and continuously improve analytical solutions
• Collaborate with data engineering, platform, SRE, and business teams to operationalize AI-driven insights
• Develop dashboards and data visualizations to communicate insights effectively to technical and non-technical stakeholders
• Drive measurable business impact through data science initiatives and analytical storytelling
• Mentor junior analysts and promote a strong data-driven culture within the organization