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Head of Analytics - Omnichannel Retail Operations

(Research Analyst)

WING BANK (CAMBODIA ) PLC
Boeng Keng Kang | Phnom Penh
  1 Post
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Head of Analytics - Omnichannel Retail Operations
WING BANK (CAMBODIA ) PLC, Boeng Keng Kang | Phnom Penh

Head of Analytics - Omnichannel Retail Operations

WING BANK (CAMBODIA ) PLC

Head of Analytics - Omnichannel Retail Operations

(Research Analyst)

WING BANK (CAMBODIA ) PLC
Recruiter active5 hours ago This Company is Actively
Hiring. Your CV will be Sent
Directly to the Company.
This Company is Actively
Hiring. Your CV will be Sent
Directly to the Company.
Cambodia - Phnom Penh
Verified This Job has been Verified as
Real by the Company.

Experience level

Manager

Job Function

Research and Development

Job Industry

Banking/ Insurance/ Microfinance

Min Education Level

Bachelor Degree

Job Type

Full Time

Job Description

A Fantastic Opportunity for ...

  • Define and implement an integrated analytics vision across store operations, e-commerce, and corporate groups
  • Set up a centralized analytics governance framework to unify KPIs, taxonomies, and data ownership across group companies
  • Build and lead a high-performing analytics team specializing in predictive, prescriptive, and real-time intelligence
  • Retail & Merchandising Analytics: SKU-level demand forecasting by store, region, and channel, Sales forecasting models using time-series, seasonality, promotional calendars, Market Basket Analysis and item affinity mapping to inform planograms and promotions and Category performance deep dives, markdown strategy insights, and shelf-space optimization
  • Store & Profitability Analytics: Store P&L modeling, operating cost structures, footfall vs. revenue analysis, New store roll-out simulations based on location intelligence, cannibalization risk, and competitive heatmaps, Inventory optimization models for in-store and DCs (distribution centers), with reordering logic.
  • Customer & Personalization Analytics: Build recommendation engines for web, app, and in-store digital kiosks, Customer segmentation based on recency, frequency, monetary value (RFM), lifestyle, channel preference, demographic data, buying patterns, etc, Cross-sell and upsell targeting models for campaigns and POS nudges, Propensity modeling for offer response, churn risk, and product category migration
  • Credit & Risk Analytics (if applicable): Develop propensity-to-pay and creditworthiness scoring for retail financing (if BNPL or credit options exist) or work with the Bank Teams to deploy the score cards, Cross leverage data sources to refine and optimize the store operations, BNPL response, working capital loan provisions for franchise outlets, revolving credit lines for customers, Analyze consumer affordability by cohort and region
  • Stakeholder Engagement: Collaborate with product, marketing, retail ops, finance, and IT teams, Influence strategy by presenting clear, actionable business insights at the CXO level and Align analytics outcomes with business objectives, store performance metrics, and loyalty goals.

Open To

Male/Female

Job Requirements

  • Master’s degree or Ph.D. in Data Science, Statistics, Operations Research, or a related field
  • Prior experience working in omnichannel retail, large format chains, or retail aggregators
  • Certifications in machine learning, forecasting, or data architecture is a plus
  • Experience working with customer data platforms (CDPs) and marketing automation tools.
  • 10+ years in data/analytics roles, with at least 3 years in an organised retail or CPG industry
  • Strong grasp of retail economics, footfall dynamics, inventory logic, last-mile operations
  • Hands-on experience with recommendation systems, RFM-based targeting, and basket-based analytics
  • Advanced proficiency in SQL, Python/R, and BI tools (Power BI, Tableau)
  • Expertise in predictive modelling, demand forecasting, classification algorithms, and inventory optimization
  • Experience with data engineering workflows, ETL pipelines, and cloud-based data environments (e.g., GCP, AWS, Azure)
  • Understanding of ML deployment pipelines, model monitoring, and feedback loops
  • Experience working with large transactional datasets, ERP systems, and retail POS data
  • Proven ability to lead analytics teams and work with cross-functional analysts
  • Strong business acumen: ability to link analytics output to P&L outcomes
  • Ability to manage multiple stakeholder groups across companies and business units
  • Exceptional storytelling with data: synthesis, visual narrative, and executive summaries.

What we can offer

Benefits

- Rewards for over performance

Highlights

- Join an experienced team

Career Opportunities

- Learn new Skills on the jobs