Lead, Data Scientist - Converse at Nike in Boston, Massachusetts

Job description

• 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.
• This role plays a critical part in advancing Converse's transformation toward a more data-driven, performance-oriented organization. As the business continues to navigate an increasingly dynamic marketplace, the Lead, Data Scientist, Performance Operations & Insights helps ensure decisions are grounded in timely, trusted, and actionable insights.
• By combining deep analytical expertise with an understanding of planning and enterprise priorities, this role enables leaders to identify risks and opportunities earlier, improve alignment across functions and geographies, and make more informed decisions that drive growth, profitability, and operational efficiency.
• Beyond delivering insights, this role helps shape the future of analytics at Converse by building scalable solutions, embedding AI-enabled capabilities into planning processes, and reinforcing a culture of performance management where outcomes are measured consistently, accountability is clear, and data drives action across the enterprise.

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

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)
• 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

Skills

Preferred

• Data Bricks and Snowflake preferred
• Sigma preferred, Tableau

Benefits

• The annual base salary for this position ranges from $126,700.00 in our lowest geographic market to $258,400.00 in our highest geographic market. Actual salary will vary based on a candidate's location, qualifications, skills and experience.
• Information about benefits can be found here.