Senior Data Analytics & BI, Global Converse

Nike•Boston, MA

5d•$107,700 - $212,600•Onsite

About The Position

The Senior, Data Analytics & BI, Global Converse is a Boston-based role responsible for delivering advanced analytics capabilities primarily supporting Supply Chain & Logistics, with additional partnership across Planning, Merchandising, Finance, and other enterprise functions. The role blends business context, technical execution, and analytical expertise to develop forecasting, optimization, and scalable analytical products, using SQL, Python, machine learning, and modern analytics platforms to solve complex business questions across the enterprise. The position also helps advance data literacy and strengthen Converse’s data science community, raising the bar for how analytics, forecasting, and AI-enabled methods are applied across the organization. The Data, Analytics & Intelligence team supports business partners through trusted data, advanced analytics, and scalable BI capabilities while modernizing Converse’s data foundation and strengthening analytical capabilities for decision-ready insights.

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 beyond one-off analysis.
Experience working with imperfect or incomplete data and developing structured 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 methodologies and results into clear recommendations for non-technical stakeholders.
Experience partnering cross-functionally and balancing priorities across multiple stakeholder groups in a dynamic business environment.
Curious, adaptable, creative problem-solving mindset, with strong attention to detail and accountability for delivery.
Proficient Python development, including 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.
Experience rapidly prototyping analytical solutions and scaling successful approaches into repeatable products or production-ready outputs.
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.
Bachelor’s degree in Business, Analytics, or a related field; suitable combinations of education, experience, and training are accepted.

Nice To Haves

Retail, consumer, or planning experience preferred.
Experience applying analytics within Supply Chain, Logistics, inventory management, order management, fulfillment, or related retail operations.
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.
Advanced understanding of BI and visualization tools; Sigma preferred, with Tableau or comparable platforms acceptable.
Solid 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, primarily for Supply Chain & Logistics and also for Planning, Merchandising, Finance, and enterprise leadership.
Build forward-looking analyses identifying trends, risks, opportunities, and potential business impacts across demand, inventory availability and productivity, order fulfillment, delivery performance, 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 translate analytical outputs into clear, executive-ready recommendations supporting growth, profitability, inventory productivity, and consumer outcomes.
Improve data quality, accessibility, governance, and usability across the modern data stack, including consistent KPI definitions and reusable semantic models.
Contribute hands-on across querying, data transformation, feature engineering, statistical modeling, machine learning, and advanced analytics workflows.
Advance data literacy and foster a stronger data science community within Converse through partnership, knowledge sharing, and practical application of modern analytical methods.
Explore and apply emerging AI capabilities where they can responsibly accelerate analysis, improve signal quality, or scale decision support.