Head of Analytics - Omnichannel Retail Operations

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Head of Analytics - Omnichannel Retail Operations

(Research Analyst)

WING BANK (CAMBODIA ) PLC

Boeng Keng Kang | Phnom Penh

1 Bài đăng

Nộp đơn ở đây

Hồ sơ công ty Công việc từ công ty này 24

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Head of Analytics - Omnichannel Retail Operations

WING BANK (CAMBODIA ) PLC, Boeng Keng Kang | Phnom Penh

Nộp đơn ở đây

Head of Analytics - Omnichannel Retail Operations

WING BANK (CAMBODIA ) PLC

Nộp đơn ở đây

Head of Analytics - Omnichannel Retail Operations

(Research Analyst)

WING BANK (CAMBODIA ) PLC

Cambodia - Phnom Penh

Boeng Keng Kang | Phnom Penh

1 Bài đăng

Hôm nay

Nộp đơn ở đây

Mức độ kinh nghiệm

Manager

Chức năng công việc

Research and Development

Ngành nghề

Banking/ Insurance/ Microfinance

Trình độ học vấn tối thiểu

Bachelor Degree

Loại công việc

Full Time

Mô tả công việc

A Good 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.

Mở Đi

Male/Female

Yêu cầu công việc

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.