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Senior Data Scientist with Retail experience

Sesheng Company
Full TimeseniorRemote
RemoteRemotePosted April 27, 2026

Job Description

Commercial Analytics Lead (Retail / CPG)

Duration:

Fulltime

Location:

India ( to work in 9 am - 5 pm EST US hours)

Must-Have Skills & Industry Experience:

#SQL #Python

#RetailAnalytics #CPG #ShopperInsights

#DataVisualization #PowerBI #BasketAnalysis #CommercialStrategy #CloudData #LoyaltyData #PromotionOptimization

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.

  • 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.

Sesheng LLC is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. We are committed to creating a diverse and inclusive environment for all employees.

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