Sr Data Scientist

As a Senior Data Scientist, you will develop and deploy machine learning and advanced analytics solutions using large-scale customer and business datasets.

The role requires strong hands-on experience with Python, SQL, Databricks, and PySpark, along with a solid understanding of Machine Learning and statistical modeling.

You will work on problems related to customer behavior, campaign effectiveness, targeting, response modeling, and business performance, helping stakeholders make better data-driven decisions.

What You'll Do

• Develop and implement Machine Learning models to solve complex business and customer analytics problems.
• Build predictive models for customer behavior, campaign response, targeting, propensity, and other business outcomes.
• Perform feature engineering, model development, validation, tuning, and performance evaluation.
• Work with large and complex datasets using Databricks and PySpark.
• Write efficient and scalable SQL for data extraction, transformation, aggregation, and analysis.
• Use Python and relevant Data Science libraries to develop analytical solutions.
• Analyze customer and campaign data to identify behavioral patterns, trends, opportunities, and areas for improvement.
• Support campaign analytics, including campaign performance measurement, customer response analysis, targeting, and effectiveness assessment.
• Translate business and marketing questions into appropriate Data Science methodologies.
• Apply statistical techniques and Machine Learning approaches to identify meaningful customer and business insights.
• Work closely with Data Engineers to prepare and leverage scalable data pipelines and analytical datasets.
• Validate models and analytical approaches using appropriate statistical and Machine Learning evaluation techniques.
• Communicate analytical findings, model results, and recommendations clearly to technical and non-technical stakeholders.
• Partner with business teams to convert analytical insights into measurable business actions and outcomes.
• Contribute to productionizing Data Science solutions and following best practices around code quality, version control, testing, and model lifecycle management.
• Mentor junior Data Scientists and contribute to the broader technical capability of the team.