eClerx - Consultant - Advanced Analytics & Predictive Modeling

The Ideal Experience Map

Between 4 to 7 years of experience in advanced analytics and predictive modeling

The ideal candidate will have hands on prior experience in developing models and awareness in concepts that help define cross-sell and up-sell strategies, market segmentation, price optimization, time to event, survival analysis, churn and customer attrition, CLV [customer lifetime value] modeling, price optimization, using tools like SAS and R.

Ideally, an attitude driven for complex project management, and an ability to display ownership and deliver data-driven projects and solutions with minimal direction.

Educational Qualifications: Preferably, Masters or a Post-graduate degree in statistics, mathematics, economics, engineering or an MBA from a reputed institute.

Roles and Responsibilities

- Display strong communication skills [written and spoken] with an ability to engage clients from the C-suite to marketing managers and understand business requirements and convert the same into technical / modeling problems for developing solutions, and deliver results in a time-bound fashion

- Ability to articulate results of statistical models and complex technical concepts in business language

- Demonstrate strong analytical and storytelling skills and the ability to find relevant insights from piles of reports, followed by interpretation of the analytical results, presentation and recommend next steps to client

- Define project scope and deliverables that support business goals; collaborate with delivery team and analytics practice lead to deliver projects

- Lead from the front by designing and developing innovative solutions to complex, challenging and first-of-its-kind problems

- Create templates for reports and visual presentations

- Audit deliverables to make sure that they are accurate and meet requirements by critically examining the data

- Travel to client locations internationally, as per the requirements, for scoping, reviews, workshops and so on

Technical and Functional Skills

1. Demonstrated knowledge of analytical and statistical techniques and their applications

2. Expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models etc

3. Expert in handling large data, cleansing and preparation for modeling

4. Working knowledge of SAS, R, and / or SPSS and its respective libraries

5. Domain knowledge of at least one vertical amongst Retail, Cable, Technology