Sr Commercial Analyst

S&S Activewear LLC•Bolingbrook, IL

4d•Hybrid

About The Position

S&S Activewear is a leading North American, tech-enabled specialty distributor of imprintable apparel. We pride ourselves on being the “critical link” that enables our 100+ brand partners to reach our hyper-fragmented base of customers. At S&S, we differentiate in the market through a customer service focus, strategic product portfolio, world-class distribution infrastructure, a collaborative growth culture and a relentless focus on technology and innovation. Our success has compounded since the Company’s humble beginnings in 1988 to a leading, multi-billion-dollar value-added distribution platform. We strive to be the apparel distributor of choice while inspiring and fostering growth for customers, employees and suppliers through our core values of service, deep relationships, innovation, continuous improvement and accountability. The Senior Commercial Analyst is a senior individual contributor who owns business intelligence and advanced analytics for material commercial segments, regions, channels, or customer portfolios. This role transforms complex and ambiguous business questions into scalable data products, decision frameworks, and actionable recommendations that improve revenue, margin, productivity, and forecast quality. The ideal candidate combines strong commercial acumen with deep technical expertise in business intelligence, data modeling, SQL, visualization, and analytics engineering. This individual works with limited guidance, influences directors and functional leaders, and serves as a technical lead and trusted advisor across Sales, Commercial Strategy and Planning, FP&A, Data Science, and enterprise data teams.

Requirements

Bachelor’s degree in Business, Economics, Finance, Analytics, Computer Science, Information Systems, Engineering, or a related field, or equivalent practical expertise.
Demonstrated success independently owning complex commercial BI and analytics solutions that influenced decisions and delivered measurable business outcomes.
Advanced Power BI expertise, including semantic modeling, DAX, Power Query, visualization design, security, deployment, refresh management, and performance tuning.
Advanced SQL skills and hands-on experience building, validating, and maintaining analytical data models; Snowflake experience is strongly preferred.
Strong knowledge of data warehousing concepts, dimensional modeling, data lineage, governance, and quality controls.
Experience applying forecasting, scenario analysis, experimentation, segmentation, or statistical methods to commercial business questions.
Strong financial and commercial acumen, including the ability to connect operational drivers to revenue, margin, and P&L outcomes.
Proven ability to influence director-level stakeholders, lead cross-functional workstreams, and convert ambiguous questions into clear recommendations and action plans.
Excellent communication, presentation, and data-storytelling skills for both technical and non-technical audiences.

Nice To Haves

Experience with Python, R, version control, APIs, cloud data platforms, or automation tools.

Responsibilities

Own the end-to-end BI and analytics roadmap for an assigned commercial segment, translating strategic priorities into scalable dashboards, data products, analytical solutions, and measurable outcomes.
Frame ambiguous business problems, define analytical approaches, reconcile conflicting signals, and develop clear options and recommendations for senior leaders.
Design, build, and maintain enterprise-grade Power BI solutions, including semantic models, data models, DAX measures, row-level security, refresh strategies, performance optimization, and governance standards.
Develop advanced SQL queries and reusable data models that integrate CRM, ERP, Snowflake, financial, and external market data into trusted analytical datasets.
Establish KPI definitions, calculation logic, data-quality thresholds, documentation, and controls to ensure consistent and reliable decision-making.
Apply forecasting, scenario modeling, segmentation, experimentation, and statistical methods to diagnose performance drivers and quantify opportunities, risks, and trade-offs.
Translate commercial performance into P&L, revenue, margin, productivity, retention, and investment impacts to guide prioritization and resource allocation.
Automate recurring reporting and decision processes, reducing manual effort and improving speed, accuracy, and adoption.
Lead weekly, monthly, and quarterly business reviews by delivering concise performance narratives, forward-looking insights, and activation recommendations.
Own deep-dive analyses across sales performance, pipeline, territory effectiveness, customer behavior, pricing, promotions, marketing initiatives, and commercial execution.
Build business cases, scenarios, and measurement plans that inform operating plans, investments, tests, and strategic initiatives.
Partner with Data Science to design analyses and experiments, interpret results, and operationalize models and recommendations within commercial workflows.
Monitor business performance and proactively identify emerging trends, risks, root causes, and growth opportunities.
Define success measures and track benefits realization for adopted recommendations and analytical products.
Act as a trusted analytics advisor to Sales and Commercial leaders, challenging assumptions and influencing commercial actions, investment choices, and prioritization.
Lead cross-functional analytical workstreams across Sales, Commercial Strategy and Planning, Merchandising, Marketing, RGM, FP&A, Data Science, BI, and Data Engineering.
Resolve competing stakeholder priorities, align teams on common metrics and analytical methods, and drive adoption of insights and tools.
Communicate complex technical and analytical concepts through clear data stories tailored to technical and non-technical audiences.
Mentor analysts, review analytical work, share best practices, and raise BI and analytics capability across the organization without direct-report responsibility.
Own data integrity, metric governance, validation processes, and issue escalation for decisions within the assigned scope.
Identify and resolve data gaps, lineage issues, and inconsistencies in partnership with data owners and engineering teams.
Lead the redesign and standardization of reporting and analytical processes, with measurable improvements in cycle time, quality, usability, and adoption.
Evaluate and pilot new BI, automation, and advanced analytics capabilities that improve commercial decision-making.
Maintain clear technical documentation, solution standards, and sustainable support models for business-critical analytics products.