Job Description

Data Scientist--

Hybrid, NJ--

Up to 109k plus benefits--

For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits

The Data Science team partners with marketing, analytics, and digital optimization teams to develop advanced analytical solutions that improve marketing effectiveness and customer engagement.

This role focuses on applying statistical modeling, experimentation, and machine learning techniques to understand customer behavior across the marketing and digital customer journey. Insights generated from this work help guide marketing strategy, customer targeting, and investment decisions.

The position operates within a modern analytics environment leveraging Amazon Redshift, AWS SageMaker, and AWS CodeCommit to build scalable analytical workflows and production-ready models.

We are seeking a Senior Data Scientist with strong statistical expertise to develop analytical frameworks, predictive models, and experimentation strategies that support marketing optimization and customer journey analysis.

The role requires a strong understanding of statistical inference, causal analysis, and predictive modeling to help translate business questions into rigorous analytical solutions. The candidate should be comfortable working with large datasets, building scalable models, and communicating analytical insights to cross-functional teams.

This position requires collaboration with marketing strategy, digital optimization, and analytics teams to ensure analytical insights are effectively integrated into business decision-making.

• Develop statistical and machine learning models to analyze customer behavior across marketing and digital channels.
• Conduct deep analytical investigations to identify drivers of customer acquisition, engagement, conversion, and retention.
• Design and evaluate marketing experiments and A/B tests to measure campaign effectiveness and customer impact.
• Apply causal inference techniques to distinguish correlation from true causal effects in marketing and customer data.
• Translate business questions into statistical analysis frameworks and modeling approaches.
• Connect analytical insights to business outcomes including revenue growth, marketing efficiency, and cost optimization.
• Build scalable analytical pipelines using Python and SQL.
• Query and analyze large datasets within Amazon Redshift.
• Develop and deploy predictive models using AWS SageMaker.
• Maintain version-controlled analytical workflows using AWS CodeCommit.
• Collaborate with marketing, analytics, and engineering teams to ensure analytical solutions support business strategy and operational decision-making.
• Present analytical findings and recommendations to technical and non-technical stakeholders.

• Master’s degree in Statistics or a related quantitative discipline such as econometrics, applied mathematics, operations research, or data science.
• Strong proficiency in Python for statistical analysis and modeling.
• Strong proficiency in SQL for large-scale data querying.
• Experience working with large datasets and advanced analytical methods.

Preferred experience includes:

• Experience in marketing analytics, customer analytics, or digital analytics.
• Experience designing and evaluating A/B tests and controlled experiments.
• Knowledge of causal inference methods and experimental design.
• Experience building production-ready machine learning models.
• Familiarity with AWS analytics and machine learning tools, including Amazon Redshift and AWS SageMaker.