What are the responsibilities and job description for the Commercial Analytics Lead (Retail / CPG) position at SESHENG LLC?
Commercial Analytics Lead (Retail / CPG)
Duration: Contract
Must-Have Skills & Industry Experience:
#SQL #Python #RetailAnalytics #CPG #ShopperInsights #DataVisualization #PowerBI #BasketAnalysis #CommercialStrategy #CloudData #LoyaltyData #PromotionOptimization
Location: New Jersey (Hybrid - Not remote)
Sesheng LLC is seeking a high-caliber Analytics Consultant for a project-based engagement. This role is centered on leveraging advanced cloud-based retail data environments to solve high-impact business challenges. You will analyze shopper transactions, basket dynamics, and loyalty data to provide the strategic intelligence needed to optimize promotions, pricing, assortment, and overall shopper engagement.
As a bridge between data and decision-making, you will partner closely with Customer Development, Shopper Marketing, and Analytics teams to transform raw datasets into clear, actionable commercial narratives.
Key Responsibilities
- Strategic Advisory: Partner with cross-functional stakeholders to translate complex business questions into structured analytical frameworks.
- Deep-Dive Analysis: Lead hands-on exploration of transaction and loyalty data to uncover insights regarding promotion ROI, trip dynamics, and basket halo effects.
- Commercial Synthesis: Convert complex findings into executive-ready insights that inform joint business planning and commercial execution.
- Standardization: Collaborate with business partners to ensure consistent KPI definitions and logic across all retail transaction datasets.
- Visual Storytelling: Design and deliver compelling dashboards, charts, and slide-ready summaries for both technical and non-technical audiences.
- Proactive Innovation: Act as a thought partner to identify emerging analytical opportunities within the data to drive future growth.
- Knowledge Management: Document methodologies and ensure a seamless knowledge transfer at the conclusion of the 26-week term.
What You Need to Succeed
- 6 years of experience managing large-scale transaction or shopper-level datasets, specifically within the Retail or CPG sectors.
- Technical Proficiency: Hands-on expertise in cloud-based analytics environments using modern tools to manipulate massive datasets.
- Analytical Rigor: A proven track record of translating loyalty and basket data into tangible commercial results.
- Communication Excellence: The ability to explain "the why" behind the data to stakeholders at all levels.
- Agility: Comfort working independently in a fast-paced, project-based consulting environment with strict timelines.
Must-Have Skills & Industry Experience
#SQL #Python #RetailAnalytics #CPG #ShopperInsights #DataVisualization #PowerBI #BasketAnalysis #CommercialStrategy #CloudData #LoyaltyData #PromotionOptimization
Core Skills & Qualifications
Required:
- Advanced proficiency in SQL and/or Python for large-scale data manipulation.
- Strong grasp of shopper metrics: penetration, frequency, trip missions, and cross-purchase behavior.
- Experience delivering end-to-end analytics projects, from initial hypothesis to final delivery.
- Background working with Customer Development, Sales, or Shopper Marketing teams.
- Proven ability to create executive-ready visualizations in Power BI, Excel, or similar tools.
Preferred:
- Direct experience with Retailer Collaborative Clouds (proprietary retailer platforms).
- Familiarity with syndicated data sources such as Circana (IRI) or Nielsen.
- Experience in a consulting-style role with defined project deliverables.