Lead, Data Scientist - Converse

Nike•Boston, MA

6d•Onsite

About The Position

The Lead, Data Scientist, EBP Performance Operations & Insights is a Boston-based role responsible for advancing global analytics and embedding more sophisticated technical capabilities into planning workflows. This role partners with numerous cross-functional stakeholders to deliver scalable, decision-oriented insights—blending business context, analytics, and technical execution to improve how performance is understood and acted upon across the enterprise.

Requirements

Strong technical foundation in data manipulation, modeling, and large-scale data analysis
Significant experience applying advanced analytical methods such as regression analysis, time-series modeling, cohort analysis, or optimization techniques
Ability to design and evaluate models that surface patterns, forecast outcomes, or quantify risk and opportunity
Proven experience using analytical rigor, AI-enabled methods, and rapid experimentation to solve complex business problems in imperfect data environments
Experience working with imperfect or incomplete data and building structured approaches to improve signal quality
Proficiency in querying, data transformation, and building reusable analytical workflows
Experience developing scalable solutions that move from one-off analysis to productionized outputs
Ability to frame ambiguous business problems into analytically tractable approaches
Strong communication skills, with the ability to clearly explain methodologies, assumptions, and implications to non-technical stakeholders
Experience partnering cross-functionally, balancing priorities across numerous stakeholder groups
Curious, adaptable, creative problem-solving mindset
Strong attention to detail and accountability for delivery
5+ years of experience in advanced analytics, data science, or related technical roles (retail/consumer preferred)
Proficient in Python development (pandas, scikit-learn, statistical modeling, optimization)
Advanced in SQL (data transformation, complex querying, data engineering concepts)
Familiarity with cloud analytics environments and modern data stacks/ platforms (Data Bricks and Snowflake preferred)
Practical application of AI/ML, including: Generative AI LLM-based workflows Agentic systems Retrieval-Augmented Generation (RAG) Forecasting and predictive modeling
Ability to rapidly prototype and scale solutions
Advanced understanding of BI and visualization tools (e.g., Sigma preferred, Tableau)
Demonstrated experience turning unstructured data into actionable insights
Experience leading and owning complex projects
Solid understanding of planning concepts such as demand, inventory, and seasonality a plus

Responsibilities

Deliver and evolve global performance insights across demand, inventory, product, and channel views
Translate complex or ambiguous business questions into structured, scalable analytics solutions + insights
Develop forward-looking analyses to identify trends, risks, and opportunities
Build and scale analytics solutions that improve speed, automation, and consistency of insights
Partner with Technology to enhance data quality, accessibility, and usability
Contribute hands-on across data modeling, querying, and advanced analytics workflows
Drive alignment on metrics, definitions, and reporting outputs across regions
Translate complex analytical outputs into clear, executive-ready recommendations
Leverage Python, SQL, machine learning, and emerging AI technologies to create scalable analytical products that accelerate decision-making across the enterprise
Act as a strategic thought partner to Planning leaders, translating complex analytical findings into clear recommendations that drive growth, profitability, inventory productivity, and consumer outcomes