Responsibilities

• Growth Infrastructure: Build and operationalize Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), and lift measurement to optimize omnichannel spend.
• Lifecycle Value & Targeting: Develop customer lifetime value (CLV) models and segmentation to inform acquisition, retention, and investment strategies.
• Actionable Insights & Campaigns: Translate analytical outputs into campaign strategies, experiments, and optimization plans across cross-functional teams.
• Experimentation Leadership: Lead experimentation strategy including A/B and multivariate tests to evaluate initiatives and product features.
• Collaboration with Stakeholders: Partner with marketing teams to turn analyses into actionable plans and measurable improvements.
• Measurement Frameworks: Define and measure the incremental impact of campaigns, promotions, and loyalty programs.
• Data-Driven Personalization: Work with large datasets to create segmentation and personalization frameworks that drive engagement and conversion.
• Cross-Ecosystem Measurement: Contribute to measurement frameworks across owned, paid, and omnichannel ecosystems.
• Engineering & Production: Collaborate with data engineering and technology teams to ensure scalable and production-ready solutions.
• Asset Development: Develop reusable data science assets, tools, and frameworks to improve efficiency and consistency.
• Communication to Leadership: Present insights and model outputs to stakeholders, including senior leadership, clearly and persuasively.
• Domain Expertise: Serve as a subject matter expert in domains such as forecasting, customer analytics, pricing, marketing analytics, or optimization.

Requirements

• Bachelor’s Degree in Data Science, Statistics, Computer Science, Engineering, Mathematics or related field or equivalent experience.
• 5+ years building and deploying machine learning or statistical models in a business setting.
• Strong knowledge of statistical methods, hypothesis testing, regression, and model evaluation.
• Experience with marketing analytics use cases like attribution, campaign measurement, personalization, or customer segmentation.
• Hands-on experimentation design and analysis experience (A/B testing, uplift modeling).
• Proficiency in Python or R with libraries such as pandas, scikit-learn, TensorFlow, PyTorch or equivalents.
• Experience with SQL and large datasets (complex queries, performance optimization).
• Track record of independently delivering end-to-end data science projects with measurable impact (3+ projects).
• Ability to communicate technical results to non-technical stakeholders via dashboards and reports.
• Strong analytical thinking, problem solving, and structured reasoning with business impact in mind.
• Collaborative mindset and cross-functional teamwork.
• Adaptability in dynamic environments with multiple priorities.
• Ownership mindset with urgency and accountability.
• Clear communication tailored to different audiences.

Preferred

• Master’s or PhD in related field.
• 6+ years in advanced analytics or ML.
• Experience deploying models to production (APIs, cloud platforms).
• Big data tech experience (Spark, Hadoop).
• Experience with MLOps, model monitoring, versioning, lifecycle management.
• Domain expertise in retail, e-commerce, pricing, or customer analytics.
• Experience leading project workstreams or mentoring juniors.
• Proven business outcomes from analytics solutions (revenue uplift, cost savings).
• Experience building MMM or MTA models and CLV modeling.
• Experience developing personalization or recommendation systems for marketing.
• Familiarity with causal inference and incrementality.
• Support experience for marketing orgs (paid media, CRM, loyalty, digital analytics).

Benefits

• Inclusive culture with associate-led Business Resource Groups
• 22 days of PTO and holidays
• Discounts, 401(k) match, wellness programs, and more