Responsibilities

• Design and deploy predictive models that optimize customer acquisition, lifetime value (LTV), and marketing spend allocation across channels.
• Develop scalable machine learning solutions that improve targeting, segmentation, and personalization.
• Build and refine experimentation frameworks, including A/B testing and causal inference methodologies, to measure and validate marketing impact.
• Partner with Marketing, Finance, and Executive Leadership to align data insights with profitability and growth objectives.
• Identify opportunities to drive measurable incremental revenue through advanced analytics and modeling.
• Create clear, executive-ready insights that translate complex analysis into actionable strategy.
• Establish best practices for marketing analytics, model monitoring, and continuous optimization.
• Collaborate cross-functionally with Data Engineering and IT to ensure data integrity, accessibility, and scalability.

Requirements

• 3+ years of experience in data science, marketing analytics, or a related quantitative role within a commercial business, preferably consumer-facing.
• Strong proficiency in Python or R and SQL and experience with statistical analysis tools (e.g., SAS, SPSS, or similar).
• Experience building and deploying machine learning models in production environments.
• Extensive practical expertise in predictive modeling, regression analysis, clustering, decision trees, neural networks, and classification methods, along with proficiency in frameworks such as TensorFlow and scikit-learn.
• Skilled in using data visualization tools like Tableau and Power BI, as well as database query languages such as SQL.
• Proficiency in big data technologies like Hadoop and Spark, as well as cloud platforms such as AWS, Azure, and Google Cloud.
• Experience designing and analyzing A/B tests and applying statistical methods for causal inference.
• Deep understanding of marketing performance metrics such as CAC, LTV, ROI, and attribution.
• Strong business acumen with a demonstrated ability to translate analytics into revenue impact.
• Excellent communication skills with the ability to interpret and communicate complex data analysis results in order to influence non-technical stakeholders.
• Advanced degree (Master’s or PhD) in Data Science, Statistics, Mathematics, Engineering, or related quantitative field preferred.

Benefits

• Direct impact on company growth and customer acquisition strategy.
• Opportunity to shape the evolution of data-driven decision-making across marketing.
• Competitive salary and comprehensive benefits package including medical, dental, vision, 401(k) with company match, paid time off, parental leave, and employee vehicle programs.
• Collaborative and inclusive culture that values innovation and diverse perspectives.