A Leading Global Analytics Company

Department/Division - Retail Analytics

Designation - Assistant Manager / Manager

Qualifications - Bachelor's Degree / MBA from Tier 1 / Masters in Statistics or Economics

- 6+ yrs of industry experience(Retail Domain).

- At least 2 years of experience in end-to-end project handling and project management.

- At least 2 years of experience in account management.

- Retail domain expertise is mandatory.

- Proficiency in the Segmentation / modeling methodology.

- High level of skills in various statistical methods used for modeling.

- Experience in Customer/Marketing /Loyalty Analytics Domain.

- Customer segmentation, purchase behavior analysis, loyalty analysis, category planning.

Technical Skills - Primary :

- Churn Modeling, Attrition Modeling, Poisson Regression, Predictive Modeling, Survival Analysis, Logistic Regression, Decision Trees.

- Proficiency in SAS, knowledge of tools like Base SAS/ STAT, GRAPH, Enterprise Miner.

Technical Skills - Desirable:

- Experience in Statistical Modeling along with Retail Analytics.

- Quick learner with good business understanding

- Web analytics

Other Skills:

- Mature approach, client interaction

- Exposure to Pre-sales work

Responsibilities :

- Will be working on various statistical modeling projects like Customer segmentation based on purchase behavior, Store sale forecasting, in Retail Analytics

- End to end analysis, which included Activity Intensity, Portfolio Segmentation, RFM scoring & probabilistic analysis (Market Basket Analysis). All these were done at Overall, Concept &

- Department level for standalone stores and malls.

- Understand the effectiveness of the promotion at Brand level for standalone stores & Malls using general analysis & ANOVA.

- Identify potential customers to assist in designing marketing strategies & locating opportunity areas for target marketing.

- Create cross-sell/upsell models for revenue generation.

- Create profitability models, deploying all drivers of customer profitability giving insights into revenue, attrition and risk behavior of customers.

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