Senior Data Scientist - Marketing

We are looking for an experienced Senior Data Scientist to partner closely with Marketing, Finance, Retail, and Product to translate marketing data into better decisions and business outcomes. Your work will help Oura improve marketing efficiency, optimize spend allocation, strengthen channel and revenue measurement foundations, and build scalable decision systems that make our go-to-market organization smarter over time.

This is a full-stack applied data science role that requires strong data foundations, pragmatic model development, and the ability to turn technical models into operational and strategic action. We are especially excited about candidates who have experience going beyond standalone modeling to build AI-enabled decision systems that influence how teams prioritize, allocate budget, and take action.

• →Develop models and optimization approaches that improve upper-funnel marketing performance, such as spend allocation, channel mix optimization, budget pacing, media efficiency measurement, audience strategy, and forecasted revenue impact.
• →Design and operationalize decision systems that help the business move from static reporting to repeatable, data-informed action, including recommendation engines, scenario planning tools, and AI-assisted workflows.
• →Lead experimentation and causal measurement across upper-funnel marketing programs, helping teams distinguish signal from noise and make better investment decisions across channels, campaigns, and retail partnerships.
• →Build and maintain trusted data foundations that unify marketing, revenue, retail, and product data across channels and systems to establish performance measurement metrics.
• →Build dashboards, reporting layers, and recurring analytical products that give leaders clear visibility into awareness and acquisition funnel health, campaign efficiency, retail performance, and revenue contribution.
• →Partner with Marketing and other stakeholders to define the highest-leverage growth and efficiency problems, translate ambiguous business questions into analytical frameworks, and drive marketing spend decisions through rigorous data science.
• →Collaborate with Data Engineering and business partners to improve data quality, instrumentation, metric definitions, and pipeline reliability across the marketing data ecosystem.
• →Apply AI/ML methods where they create practical leverage, including predictive modeling, optimization, and LLM-enabled workflows that improve decision speed, quality, or scale.
• →Translate complex analytical work into clear recommendations for non-technical and executive stakeholders, influencing roadmap, budget, and growth strategy decisions.
• →Help raise the technical bar for the team through strong project ownership, documentation, peer review, mentoring, and thoughtful cross-functional collaboration.

We would love to have you on our team if you have:

• 6+ years of experience in data science, machine learning, or advanced analytics, with a track record of owning high-impact business problems end to end.
• Strong domain experience supporting Marketing, Growth, Retail, or other go-to-market functions in a consumer, e-commerce, retail, or digital business.
• Hands-on experience building marketing data science solutions such as spend optimization models, channel or campaign measurement frameworks, media mix or incrementality approaches, propensity models, budget planning systems, or upper-funnel decisioning systems.
• Demonstrated experience building not just models, but decision systems that operationalize analytical outputs into business workflows and recurring decisions.
• Proven experience of data engineering intuition, including experience unifying and transforming data across multiple systems to create reliable, scalable datasets for downstream analysis, experimentation, and modeling.
• Experience with experimentation, causal inference, forecasting, and optimization methods used to support business planning and growth investment decisions.
• Strong proficiency in SQL (dbt) and Python, with experience building analytical data models, machine learning workflows, and production-quality measurement systems.
• Experience applying AI techniques in practical business settings, ideally including LLM-enabled workflows, recommendation systems, decision support tools, or other AI-native products that augment human decision-making.
• Experience working with modern cloud and data platforms such as Databricks, AWS, dbt, Snowflake, or similar tools.
• Proven ability to communicate complex analytical concepts clearly to non-technical partners and to translate model outputs into recommendations the business can act on.
• Proven ability to partner effectively with cross-functional and distributed teams in fast-moving environments.

• Experience in e-commerce, DTC, retail, or omnichannel growth environments.
• Experience with marketing mix modeling, incrementality testing, attribution, or budget planning workflows.
• Experience connecting marketing, retail, and commercial performance data to downstream revenue outcomes.
• Experience in digital health, consumer technology, or wearable products.
• Experience mentoring other data scientists and helping shape cross-functional analytical roadmaps.