Lead Data Scientist
Nike
About the role
WHO WE ARE LOOKING FOR
We are looking for a Lead Data Scientist to advance state-of-the-art recommendation systems. This role sits at the intersection of machine learning, optimization, generative AI, and decision intelligence that help customers and partners discover the right products, optimize assortments, and make informed purchasing decisions. You will lead the development of innovative recommendation solutions that connect customers and partners with the most relevant products, using machine learning, optimization, and AI-assisted workflows to create personalized, data-driven experiences at scale.
You are passionate about solving complex business problems, translating ambiguous requirements into production-ready systems, and leading cross-functional teams through innovation.
You thrive in environments where data science, AIML engineering, product management, and user experience come together to create impactful customer experiences.
WHAT YOU BRING
Master’s degree in Computer Science, Operations Research, Statistics, Applied Mathematics, Engineering, or a related field. Will accept any suitable combination of education, experience or training
5+ years of experience leading the design, development, and deployment of data science, machine learning, optimization, and operations research models at scale
Strong proficiency in Python and experience leveraging machine learning frameworks such as PyTorch, TensorFlow
Deep knowledge of recommendation systems, ranking models, personalization, and predictive analytics
Experience designing and evaluating large-scale experimentation platforms and A/B testing methodologies
Strong background in optimization techniques, including linear programming, mixed-integer optimization, reinforcement learning, and multi-objective optimization is preferred
Experience building solutions using Agentic AI, Large Language Models (LLMs), tool orchestration and evaluating Agentic systems using automated and human-in-the-loop approaches
Demonstrated expertise in modern recommender systems and emerging LLM/GenAI techniques, with the ability to lead the design of scalable personalization solutions combining traditional recommendation methods, embeddings, semantic retrieval, ranking, and generative approaches.
Experience with cloud-native ML platforms such as Databricks, AWS SageMaker
Demonstrated ability to lead complex cross-functional initiatives
Strong communication skills
WHAT YOU WILL WORK ON
As a Lead Data Scientist, you will lead the scientific strategy and technical execution for AI-powered recommendations. Your work will span predictive modeling, recommendation systems, optimization engines, and generative AI experiences.
Key responsibilities include:
Develop and deploy advanced recommendation models that deliver personalized product experiences aligned with customer needs and partner business objectives
Design and implement optimization frameworks that balance customer preferences, inventory availability, profitability, and operational constraints
Lead the development of generative AI capabilities that enhance recommendation experiences through intelligent insights, explanations, and decision support
Establish experimentation and measurement frameworks to evaluate recommendation quality, customer engagement, business impact, and AI effectiveness
Partner closely with product managers, engineers, designers, and business stakeholders to define strategy, prioritize opportunities, and execute against the product roadmap
Drive scientific rigor through model evaluation, offline benchmarking, online experimentation, and continuous improvement
Mentor and develop data scientists and machine learning engineers, fostering technical excellence and a culture of learning
Communicate complex analytical findings and strategic recommendations to technical and non-technical audiences, including senior leadership
We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form.
Responsibilities
- Lead the design and deployment of personalized recommendation systems.
- Build optimization frameworks that balance customer preferences, inventory, profitability, and operational constraints.
- Develop generative AI capabilities for recommendation insights and decision support.
- Establish experimentation and measurement frameworks for recommendation quality and business impact.
- Partner with product, engineering, design, and business teams to set strategy and deliver the product roadmap.
- Evaluate models through offline benchmarking, online experimentation, and continuous improvement.
- Mentor data scientists and machine learning engineers.
- Communicate analytical findings and recommendations to technical and non-technical audiences.
Qualifications
- Master’s degree in a related field, or a suitable combination of education, experience, or training.
- At least 5 years of experience leading the design, development, and deployment of data science, machine learning, optimization, or operations research models at scale.
- Strong Python proficiency and experience with PyTorch or TensorFlow.
- Expertise in recommendation systems, ranking, personalization, and predictive analytics.
- Experience designing large-scale experimentation platforms and A/B testing methodologies.
- Experience with agentic AI, large language models, tool orchestration, and evaluation of agentic systems.
- Experience with cloud-native ML platforms such as Databricks or AWS SageMaker.
- Strong cross-functional leadership and communication skills.
Skills mentioned
About Nike
NIKE, Inc. is a purpose driven company fueled by a shared commitment to move the world forward through the power of sport. Guided by our mission to bring inspiration and innovation to every athlete* in the world, we champion sport’s values of inclusion and diversity while pushing boundaries to shape the future. At Nike, every teammate plays a role. We operate with an athlete’s mindset — working together, embracing our differences, and demanding more of ourselves and each other to drive collective success. Whether you’re building products, platforms, experiences or systems, your work contributes to something bigger: making athlete* dreams real. Explore opportunities at careers.nike.com and join our Talent Community at https://nikeats.avature.net/niketalentcommunity. *If you have a body, you are an athlete.
H-1B sponsorship history
Historical employer filing data was found for Nike. The employer record includes 2,365 historical certified applications. This is employer-level history, not a guarantee that this role currently offers sponsorship.