WHO YOU’LL WORK WITH
You will partner with globally distributed engineering, product, and program teams to ensure that the ecosystem of services remains loosely coupled, independently scalable, and aligned with business needs. You will work with your peers to develop key innovation features and report to the Engineering Manager for Marketing Technology.
WHO WE ARE LOOKING FOR
We are seeking a Senior Data Scientist who will drive advanced analytics, predictive modeling, and machine learning solutions across Marketing Technology’s global digital and enterprise ecosystem. You bring deep technical expertise combined with business acumen, enabling you to translate complex data into actionable insights and high-impact models. You thrive in ambiguous environments, collaborate naturally with cross-functional partners, and elevate data maturity through innovation, quality, and thoughtful leadership.
Skillset Required
Bachelor’s degree in related field. Will accept any suitable combination of education, experience and training.
5+ years of experience in data science, machine learning, applied statistics, or advanced analytics.
Strong experience with customer, marketing, and digital analytics domains, including segmentation, personalization, propensity modeling, churn prediction, customer lifetime value (CLV/LTV), attribution, media measurement, and audience targeting.
Strong proficiency in Python, SQL, and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost).
Experience with Generative AI, LLMs, RAG architectures, AI agents, prompt engineering, and model evaluation frameworks, including responsible AI considerations.
Experience deploying ML models into production environments and working with cloud platforms (AWS, Azure, or GCP), Databricks ML, MLflow, Spark, Delta Lake, Snowpark, and Vector Databases.
Expertise in predictive modeling, optimization, experimentation, and advanced statistical methods.
Strong understanding of data engineering concepts, feature stores, and ML Ops principles.
Familiar with Databricks, Snowflake and other database foundational tools.
Experience with visualization tools and storytelling for technical and non-technical audiences.
Ability to work cross-functionally, influence stakeholders, and translate complex analysis into actionable strategies.
Strong communication skills, curiosity, ownership mindset, and commitment to quality.
WHAT YOU’LL WORK ON
Build and evolve membership intelligence, audience targeting, personalization, and consumer decisioning capabilities across marketing channels.
Develop AI-powered marketing intelligence solutions, including audience recommendations, content optimization, and campaign effectiveness measurement.
Lead the design of LLM and Generative AI use cases within Martech, ensuring scalable, secure, and measurable business outcomes.
Drive adoption of AI-native data science practices and establish best practices for model governance, evaluation, and operational excellence.
Build a better practice around our marketing targeting intelligence and able to manage of targeting / data science models used from membership (lifecycle/churn/LTV/affinities) for advertising and comms.
Develop, deploy, and maintain machine learning models that accelerate decision-making across product, marketplace, consumer, and operational teams.
Partner with engineering, analytics, and product teams to build scalable data science pipelines and integrate models into production environments.
Conduct exploratory analysis, identify meaningful patterns, and translate findings into clear narratives and recommendations.
Ensure model quality through rigorous testing, validation, drift monitoring, and performance measurement.
Drive experimentation frameworks, A/B testing design, and causal inference models to inform product and business strategy.
Collaborate with Nike Technology partners to align with enterprise data, ML, and platform standards.
Mentor junior and mid-level data scientists and analysts, fostering excellence in modeling, coding, and problem-solving.
Evaluate new tools, frameworks, and techniques; lead proofs of concept and guide strategic adoption of data science capabilities.
Skills Required
- Bachelor's degree in related field or equivalent combination of education, experience and training.
- 5+ years experience in data science, machine learning, applied statistics, or advanced analytics.
- Strong experience in customer, marketing, and digital analytics (segmentation, personalization, propensity, churn, CLV, attribution, media measurement).
- Strong proficiency in Python and SQL.
- Proficiency with ML frameworks: scikit-learn, TensorFlow, PyTorch, XGBoost.
- Experience with Generative AI, LLMs, RAG architectures, AI agents, and prompt engineering.
- Experience deploying ML models to production and working with cloud platforms (AWS, Azure, or GCP).
- Experience with Databricks ML, MLflow, Spark, Delta Lake, Snowpark, and Vector Databases.
- Expertise in predictive modeling, optimization, experimentation, and advanced statistical methods.
- Strong understanding of data engineering concepts, feature stores, and MLOps principles.
- Familiarity with Databricks and Snowflake; experience communicating results and creating visualizations for technical and non-technical audiences.
Nike Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Nike and has not been reviewed or approved by Nike.
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Retirement Support — A 401(k) with a company match is complemented by options such as a Mega Backdoor Roth and deferred compensation for eligible earners. Financial coaching and structured savings programs support long-term financial security.
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Equity Value & Accessibility — An Employee Stock Purchase Plan with a stock discount sits alongside broad-based equity vehicles like RSUs and non-qualified stock options. These avenues expand wealth-building opportunities beyond base pay.
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Parental & Family Support — Paid parental leave includes maternity and paternity time, recently expanded in the U.S. to 16 weeks and extended to part-time retail teammates. Additional supports include childcare assistance at select locations and family-building benefits such as fertility, surrogacy, and adoption.
Nike Insights
What We Do
At NIKE, Inc., we innovate to serve athletes*. Every teammate - from coder to creator - plays a role in making these athletes’ dreams real. Our tech, data, and digital teams push limits every day, building the future of sport and the tools that drive it. Here, curiosity is fuel. Innovation is the game plan. Different perspectives keep us on the offense. You’ll solve challenges worth tackling, grow fast and belong to a team that backs you to do the right thing. Bring your drive. Bring your bold. Let’s move the world, together. Take your first step at nike.com/careers * If you have a body, you’re an athlete.
Why Work With Us
At NIKE, Inc., your dedication fuels the future of sport. There is a sense of pride that comes from representing an iconic brand and shaping its future. Here, we treat every day as a new opportunity to push boundaries, ask tough questions and share whole-hearted convictions. We are a team – united by the belief that anything is possible.
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