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.
Required Qualifications
- 4+ years of professional experience in Data Science / Machine Learning / Advanced Analytics.
- Strong hands-on programming experience in Python.
- Strong hands-on SQL skills, including complex joins, aggregations, transformations, and analysis of large datasets.
- Mandatory hands-on experience with Databricks.
- Strong experience with PySpark / Apache Spark and distributed data processing.
- Strong foundation in Machine Learning and predictive modeling.
- Hands-on experience with:
- Classification
- Regression
- Feature engineering
- Model selection
- Model validation
- Hyperparameter tuning
- Model evaluation
- Strong understanding of statistics and applied statistical modeling.
- Experience working with large-scale datasets in an enterprise environment.
- Experience applying Data Science to customer, marketing, campaign, or business analytics problems.
- Experience analyzing campaign performance, customer response, targeting, propensity, or marketing effectiveness.
- Strong ability to translate business problems into analytical solutions.
- Ability to communicate technical concepts and analytical findings to business stakeholders.
Preferred Qualifications
- Experience in customer analytics, marketing analytics, CRM, loyalty, retail, consumer, or other customer-centric domains.
- Experience with propensity, response, churn, conversion, or targeting models.
- Experience with customer segmentation and behavioral analytics.
- Experience working with Databricks-based Data Science environments.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Experience with MLflow or similar model lifecycle/experiment tracking platforms.
- Familiarity with data visualization and communicating insights through dashboards and presentations.
- Experience working in Agile / cross-functional Data Science teams.
- Master's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related quantitative field.