Senior Data Scientist

Key Responsibilities:

1. Machine Learning & Advanced Analytics

• Design, develop, deploy, and monitor machine learning models.
• Build predictive models for customer acquisition, propensity scoring, response modeling, cross-sell/up-sell, churn prediction, customer lifetime value (CLV), and risk-adjusted marketing strategies.
• Apply statistical techniques and machine learning algorithms to solve complex business problems.
• Conduct model validation, performance monitoring, and periodic recalibration. • Develop customer segmentation frameworks and targeting strategies.
• Design and execute A/B testing and experimentation frameworks.

2. Data Analysis & Business Insights

• Perform exploratory data analysis (EDA) on large structured and unstructured datasets. • Build automated reporting and analytical frameworks to support business decision-making. • Identify trends, opportunities, and risks through advanced data analysis.
• Present insights and recommendations to senior stakeholders in a clear and concise manner.

3. Data Engineering & Cloud Analytics

• Optimize SQL queries and data processing for large-scale datasets.
• Collaborate with data engineering teams to ensure high-quality and reliable data assets. • Ensure data governance, quality, and consistency across analytical solutions.

4. Model Deployment & MLOps

• Support end-to-end model lifecycle management from development to production deployment.
• Work with engineering teams to operationalize machine learning solutions.
• Implement model monitoring, drift detection, and performance tracking mechanisms. • Contribute to best practices in MLOps and model governance.

Preferred Tech Stack:

• Programming & Data Analysis Python, SQL, PySpark, Jupyter Notebook
• Machine Learning & Statistical Modelling - Scikit-learn, XGBoost, LightGBM, CatBoost, Statsmodels, Regression, Clustering, Mlflow, Neural Networks
• Customer Analytics - Customer Segmentation, Propensity Modelling, Cross-Sell Models, Churn Prediction, Customer Lifetime Value (CLV), Campaign Measurement, Attribution Modelling, A/B Testing, Uplift Modelling, Recommendation Systems
• Data Warehousing & Databases - Google BigQuery (Mandatory), PostgreSQL, MySQL, SQL Server
• Cloud Platforms – BigQuery, Cloud Run, Vertex AIRole & responsibilities

Preferred candidate profile