[All remote jobs](https://jobicy.com/jobs.md)[![ŌURA logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2026/07/011c99434cd6-221.webp)](https://jobicy.com/company/oura.md)[ŌURA](https://jobicy.com/company/oura.md) # Senior Data Scientist – Marketing Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/oura.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUSD 147,900–203k / yrDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceDirectorPublished28 Oct 2026Apply before27 Nov 2026Listing views52Application actions3Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. Oura is seeking a senior data scientist to improve marketing efficiency, measurement, budget allocation, and revenue forecasting across marketing, retail, finance, and product. The role combines applied machine learning, causal inference, experimentation, optimization, and reliable marketing data foundations. The successful candidate will turn models into operational decision systems, dashboards, recommendations, and AI-enabled workflows for non-technical stakeholders. This is a highly cross-functional senior individual-contributor position requiring strong SQL, Python, dbt, cloud-platform, and communication capabilities. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThe position requires end-to-end ownership of complex marketing science problems, including causal measurement, forecasting, optimization, and production-quality data systems. It also demands strategic influence across several business functions and the ability to operationalize analytical outputs. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$175,450US market range (per year)$155k–$215k0$236.50k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses annual US pay bands of $147,900–$203,000, varying by location tier. The displayed job median is the midpoint of the overall disclosed range. Estimated US market compensation for a senior marketing data scientist is $155,000–$215,000 per year. ## Core skills Skills and capabilities most closely associated with this opportunity. [Marketing analytics](https://jobicy.com/jobs?search_keywords=Marketing%20analytics.md)[Causal inference](https://jobicy.com/jobs?search_keywords=Causal%20inference.md)[Experiment design](https://jobicy.com/jobs?search_keywords=Experiment%20design.md)[Media mix modeling](https://jobicy.com/jobs?search_keywords=Media%20mix%20modeling.md)[Marketing optimization](https://jobicy.com/jobs?search_keywords=Marketing%20optimization.md)[Revenue forecasting](https://jobicy.com/jobs?search_keywords=Revenue%20forecasting.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[dbt](https://jobicy.com/jobs?search_keywords=dbt.md)[Snowflake](https://jobicy.com/jobs?search_keywords=Snowflake.md)[Databricks](https://jobicy.com/jobs?search_keywords=Databricks.md)[AWS](https://jobicy.com/jobs?search_keywords=AWS.md)[Machine learning](https://jobicy.com/jobs?search_keywords=Machine%20learning.md)[Data visualization](https://jobicy.com/jobs?search_keywords=Data%20visualization.md)[Stakeholder management](https://jobicy.com/jobs?search_keywords=Stakeholder%20management.md) Sample interview questionsHow would you evaluate whether an upper-funnel marketing campaign caused incremental revenue rather than simply correlating with it?I would first define the decision, target population, outcome window, and primary success metric. Where feasible, I would use a randomized geo, audience, or holdout experiment; otherwise, I would apply a quasi-experimental design such as difference-in-differences or matched markets, validate assumptions, quantify uncertainty, and translate the estimated lift into an investment recommendation. Describe your approach to building a marketing spend allocation model. I would begin with reliable channel, campaign, cost, conversion, and downstream revenue data at an appropriate grain. I would estimate response curves and marginal returns while accounting for saturation, seasonality, lag effects, and uncertainty, then optimize allocations subject to practical constraints such as minimum commitments, budgets, and operational capacity. The model would be delivered through scenario planning rather than as a one-time analysis. How do you make analytical models useful to non-technical marketing leaders? I focus on the decision the stakeholder needs to make and present a concise recommendation, expected impact, assumptions, risks, and alternatives. I use clear visuals and scenario comparisons, document metric definitions, and provide an operational workflow so recommendations can be reviewed and acted on repeatedly. What practices would you use to create trusted marketing and revenue datasets? I would establish shared business definitions, model data in dbt, add source freshness and quality tests, reconcile key metrics to systems of record, and document lineage and known limitations. I would also partner with engineering and business owners to improve instrumentation and establish ownership for metric changes. Where can LLM-enabled workflows add value in a marketing data science organization? LLMs can accelerate analysis intake, campaign taxonomy normalization, insight summarization, and self-service exploration when grounded in governed data and deterministic calculations. I would use retrieval, access controls, evaluation datasets, monitoring, and human review for consequential recommendations, while reserving statistical models for estimation and optimization tasks. Opportunity details ## About this role. Our mission at Oura is to empower every person to own their inner potential. Our award-winning products help our global community gain a deeper knowledge of their readiness, activity, and sleep quality by using their Oura Ring and its connected app. We’ve helped millions of people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles. Empowering the world starts with living [our values](https://ouraring.com/about-us) and empowering our team. As a quickly growing company focused on helping people live healthier and happier lives, we ensure that our team members have what they need to do their best work — both in and out of the office. 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. ### What You Will Do * 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. ### Requirements 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. ### Nice to Have * 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. ### Benefits At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health. What we offer: * Competitive salary and equity packages * Health, dental, vision insurance, and mental health resources * An Oura Ring of your own plus employee discounts for friends & family * 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off * Paid sick leave and parental leave Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates’ pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future. * Region 1 $172,550 – $203,000 * Region 2 $158,950 – $187,000 * Region 3 $147,900 – $174,000 A recruiter can determine your zones/tiers based on your U.S. location. We are not considering candidates residing in the following states: Alaska (AK), Delaware (DE), Iowa (IA), Mississippi (MS), Nebraska (NE), South Dakota (SD), West Virginia (WV), and Wisconsin (WI) Oura is proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees. Individuals seeking employment at Oura are considered without regard to age, ancestry, color, gender (including pregnancy, childbirth, or related medical conditions), gender identity or expression, genetic information, marital status, medical condition, mental or physical disability, national origin, protected family care or medical leave status, race, religion (including beliefs and practices or the absence thereof), sexual orientation, military or veteran status, or any other characteristic protected by federal, state, or local laws. We will not tolerate discrimination or harassment based on any of these characteristics. We will work to ensure individuals with disabilities are provided reasonable accommodation to participate in the interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Disclaimer: Beware of fake job offers! We’ve been alerted to scammers posing as ŌURA recruiters, especially for remote roles. Please note: * Our jobs are listed only on the ŌURA Careers page and trusted job boards. * We will never ask for personal information like ID or payment for equipment upfront. * Official offers are sent through Docusign after a verbal offer, not via text or email. Stay cautious and protect your personal details. To all recruitment agencies: Oura does not accept agency resumes. Please do not forward resumes to our jobs alias, Oura employees, or any other organization’s location. Oura is not responsible for any fees related to unsolicited resumes. 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