Senior Data Analytics & BI, Global Converse

Nike•Boston, MA

About The Position

The Senior, Data Analytics & BI, Global Converse is a Boston-based role that delivers advanced analytics capabilities primarily for Supply Chain & Logistics, while partnering with Planning, Merchandising, Finance, and other enterprise functions. The role combines business context, technical execution, and analytical expertise to develop forecasting, optimization, and scalable analytical products using SQL, Python, machine learning, and modern analytics platforms. The position develops decision-ready dashboards, KPI frameworks, self-service analytics, reusable workflows, models, and data products that improve operational and strategic decisions. It also helps strengthen data quality, governance, accessibility, and data literacy across Converse, and advances the practical use of analytics, forecasting, and AI-enabled methods. The role translates complex business questions and analytical findings into clear recommendations for stakeholders and leaders.

Requirements

At least 5 years of experience in advanced analytics, data science, business analytics, BI, or related technical roles.
Strong technical foundation in data manipulation, statistical modeling, forecasting, optimization, and large-scale data analysis.
Significant experience applying advanced analytical methods such as regression analysis, time-series modeling, cohort analysis, machine learning, or optimization techniques.
Ability to design, evaluate, and explain models that surface patterns, forecast outcomes, quantify risk, and identify business opportunities.
Proficiency in SQL and Python, including building reusable analytical workflows and scalable solutions.
Experience working with imperfect or incomplete data and developing approaches to improve signal quality, reliability, and interpretability.
Ability to frame ambiguous business problems analytically and communicate assumptions, tradeoffs, and implications clearly.
Strong communication skills and ability to translate technical methods and results into recommendations for non-technical stakeholders.
Experience partnering cross-functionally and balancing priorities across multiple stakeholder groups.
Curious, adaptable, creative problem-solving mindset, with attention to detail and accountability for delivery.
Bachelor’s degree in Business, Analytics, or a related field; suitable combinations of education, experience, and training will be accepted.

Nice To Haves

Retail, consumer, or planning experience.
Experience applying analytics within Supply Chain, Logistics, inventory management, order management, fulfillment, or related retail operations.
Python development experience with pandas, scikit-learn, statistical modeling, forecasting, and optimization techniques.
Advanced SQL skills, including complex querying, data transformation, analytical modeling, and exposure to data engineering concepts.
Familiarity with cloud analytics environments and modern data platforms, including Databricks and Snowflake.
Practical experience applying AI/ML methods, particularly forecasting, predictive modeling, and optimization.
Exposure to Generative AI, LLM-based workflows, agentic systems, or Retrieval-Augmented Generation.
Experience rapidly prototyping analytical solutions and scaling successful approaches into repeatable products or production-ready outputs.
Advanced understanding of BI and visualization tools; Sigma preferred, with Tableau or comparable platforms acceptable.
Demonstrated ability to turn structured and unstructured data into actionable insights that influence business decisions.
Experience owning complex projects from problem framing through delivery, adoption, and continuous improvement.
Understanding of planning concepts such as demand, inventory, seasonality, performance management, and business forecasting.

Responsibilities

Develop, maintain, and evolve analytics products and capabilities that improve operational and strategic decision-making.
Develop and evolve decision-ready dashboards, KPI frameworks, and self-service analytics products for Supply Chain & Logistics partners.
Access, analyze, and model Converse data using SQL, Python, and related analytical tools to generate actionable business insights.
Translate complex or ambiguous business questions into structured, scalable analytics solutions supporting Supply Chain & Logistics and other enterprise functions.
Build forward-looking analyses to identify trends, risks, opportunities, and potential business impacts across demand, inventory, fulfillment, delivery, product, channel, and financial performance.
Create reusable analytical workflows, models, and data products that improve the speed, automation, consistency, and scalability of insight generation.
Partner with business stakeholders to turn analytical outputs into executive-ready recommendations supporting growth, profitability, inventory productivity, and consumer outcomes.
Improve data quality, accessibility, governance, and usability, including consistent KPI definitions and reusable semantic models.
Contribute hands-on to querying, data transformation, feature engineering, statistical modeling, machine learning, and advanced analytics workflows.
Advance data literacy and foster a stronger data science community through partnership and knowledge sharing.
Explore and apply emerging AI capabilities where they can responsibly accelerate analysis, improve signal quality, or scale decision support.