Senior Data Scientist

Role Overview

The Lead Data Scientist is responsible for developing and deploying advanced AI/ML models, leveraging statistical techniques, machine learning, and deep learning to extract actionable  insights. This role requires strong expertise in Python-based AI/ML development, big data processing, and cloud-based AI platforms (Databricks, Azure ML, AWS SageMaker, GCP Vertex AI).

Key Responsibilities

• Data Exploration & Feature Engineering

• Perform thorough Exploratory Data Analysis (EDA) and identify key variables, patterns, and anomalies.
• Engineer and select features for optimal model performance, leveraging domain understanding.

• Machine Learning & Statistical Modelling

• Implement both classical ML methods (regression, clustering, time-series forecasting) and advanced algorithms (XGBoost, LightGBM).
• Address computer vision, NLP, and generative tasks using PyTorch, TensorFlow, or Transformer-based models.

• Model Deployment & MLOps

• Integrate CI/CD pipelines for ML models using platforms like MLflow, Kubeflow, or SageMaker Pipelines.
• Monitor model performance over time and manage retraining to mitigate drift.

• Business Insights & Decision Support

• Communicate analytical findings to key stakeholders in clear, actionable terms.
• Provide data-driven guidance to inform product strategies and business initiatives.

• Ethical AI & Governance

• Ensure compliance with regulations (GDPR) and implement bias mitigation.
• Employ model explainability methods (SHAP, LIME) and adopt best practices for responsible AI