NIKE, Inc.チームの 一員になる
NIKE, Inc.の仕事は、世界トップクラスのアスリートたちにウェアやシューズを提供することだけではありません。ここは自分の潜在力を探求し、限界を取り払って、可能性を大きく広げることができる職場です。Nikeが求めているのは、意欲を持って成長し、自分の頭で考え、夢を思い描き、新しく創造できる人材。多様性を武器に創意工夫を奨励することで、企業文化を発展させています。Nikeブランドは、成功に向かって努力を続ける人や、チームを率いるリーダーや、大きな目標を思い描ける人材を求めています。常に進化し続ける仕事にはやりがいがあり、NIKE, Inc.では従業員一人ひとりが各々のスキルと情熱を日々の業務に注いでいます。
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.
私たちの採用プロセス
01 応募
私たちのチームは、多様なスキルセット、知識、意見、アイデア、バックグラウンドを持つメンバーで構成されています。 職務内容、部門、チームを確認して、自分に合った役割を見つけましょう。
02 採用担当者に会う、または評価を受ける
コーポレートの職務を選んだ場合、面接プロセスを開始するために採用担当者が連絡を取り、面接が終了するまでの間、あなたの主な窓口となります。 リテール職の場合は、チャットとクイズを含む対話型の評価を行うことになります。所要時間は約10~20分です。 職務に関わらず、私たちは皆さんの人となりを知りたいと思っています。世界トップクラスのサービスに対する考え方や、あなたの独自性について遠慮なく話してください。
03 面接
Nikeについて調べ、Nikeが何を求めているのかを理解し、あなたの人となりや経歴について詳しく知るために設定された質問に答えられるよう準備し、自信を持ってこのステージに臨んでください。