Analytics is a competitive differentiator for Converse and is fundamentally changing how the company serves athletes and consumers around the world! Our Converse Data and Analytics team builds analytic-based solutions to manage the marketplace and optimize the supply chain. Using big data, advanced analytics and innovative technology, the team strives to ensure that Converse gets the right product to the right place at the right time for the consumers
Who we are looking for
We are looking for a Senior Data Scientist to join our Enterprise Data Analytics team within Insights Data Science and Analytics focused on Converse’s overall growth over the next several years. This role will be part of a multi-functional agile squad responsible for using predictive analytics, enhance decision making and drive to action against our strategic priorities. Does this sound like you?
The candidate needs to be a dependable teammate with strong hands-on analytics experience, drive, and curiosity. You know how to rise above the numbers and explain the crucial insights to users at all levels. You simplify and distill business complexity into testable hypotheses and scalable solutions. While you are well versed in a plethora of sophisticated modeling techniques, you can identify the technique optimal for the task at hand based on the business requirements, your knowledge of the data and the technique’s assumptions, interpretability and robustness. You ask good questions, are continually learning as well as finding opportunities to share knowledge with others!
What you will work on
If this is you, you will be part of an Enterprise Data Science squad. We deliver scalable solutions to power data driven automated decision making on a variety of planning problems and other related business decisions. Specifically, you will:
- Join a team that is responsible for building models that uncover insights consumer preferences for products to inform Converse’s business teams and organizations.
- Develop new sophisticated algorithms and improve existing approaches based on statistical/econometric methods, machine learning techniques and big data solutions to forecast
- Work closely across different businesses to answer key questions about how to design the best products, line plans, and assortments to serve athletes and consumer experience.
- Ideate, develop, and operationalize algorithmic solutions for bringing a consumer lens to key decisions facing Product Creation, Merchandising, different planning, Operations, and consumer teams.
- Stay up to date on relevant industry trends and pull from your generalist data scientist toolkit to identify the right data science approach to each problem you encounter.
- Support the adoption of analytic products through effective storytelling and collaboration with key partners.
- Participate in a continuous learning environment within the analytics community through persistent development of new skills and sharing of knowledge through mentorships and contributions to the open-source community.
Who you will work with
You will work with the Director of Data and Analytics while partnering daily with fellow data scientists, data analysts, engineers and product owner on your squad.
You will collaborate across the broader organization with business teams in Demand and Supply Management as well as other data, analytics and technology functions at Nike.
What you bring
- Advanced quantitative degree (Statistics, Mathematics, Economics, Computer Science or related field) or equivalent combination of education, experience or training.
- Advanced proficiency in Python for data analysis, statistical modeling, and machine learning, with hands-on experience using libraries such as Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow, or PyTorch.
- Expertise in building, training, scoring, tuning, and deploying predictive models at enterprise scale, with a strong understanding of model lifecycle management in production environments.
- Experience with modern data platforms including Snowflake for scalable data warehousing and Databricks for collaborative data science and machine learning workflows.
- Proven ability to design and implement statistical and machine learning models to solve complex business problems, including regression, classification, clustering, and time-series forecasting.
- Familiarity with mainstream tools and packages across the Data Science/Analytics lifecycle, including model versioning, experiment tracking (e.g., MLflow), and automated model retraining pipelines.
- Strong understanding of data engineering principles, enabling seamless collaboration with engineering teams to ensure robust data pipelines and model integration.
- An ability to communicate insights and model outcomes effectively to technical and non-technical stakeholders, driving data-informed decision-making.
- A passion for continuous learning and staying current with emerging trends in data science, machine learning, and AI.
- Exposure to the Monthly business planning process in Retail and Supply chain would be an advantage.
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.
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