Associate - Marketing Modeling/Analytics - BFSI

Roles and Responsibilities

- Develop industry-leading quantitative models, using cutting edge analytical approaches, techniques and algorithms

- Worked extensively on Customer and Marketing Analytics Strategies

- Quantify the impact to marketing and media activities on campaign

- Offer optimization through campaign analytics

- Marketing Mix Modeling

- Recommendations on marketing efficiencies on Customer Acquisition

- Churn Attrition propensity model

- Cross Sell Up Sell Model Campaign Management (Campaign Designing, execution, and evaluation)

- Customer Lifetime Value Analysis

- Customer Segmentation

- Must have worked on the below techniques and algorithms like:-

- Econometric Models

- Time Series Models

- Artificial Intelligence

- Numerical Methods

- Leverage appropriate techniques for Model Monitoring & Validation

- Perform advanced quantitative and statistical analysis of large datasets

Desired Candidate Profile :

- Deep quantitative & programming background with at least a masters degree (M.S., Ph.D.) in a highly numerate discipline like Statistics, Economics, Computer Science, Mathematics, Operations Research, etc. from Tier 1 Educational Institutes in India (ISI, Delhi School of Economics, etc.) or abroad

Required Candidate Skills:-

- 4 to 8 years of related experience in leading MNCs of global repute

- Developed Marketing OR Customer Models

- Hands on experience with Machine Learning and Artificial Intelligence, Analytics

- Ability to write code and develop production ready analytical applications

- Significant experience working with very large scale (structured and unstructured) data

- Expertise in at least one of the following programming languages like Python, R

- Excellent written and oral communication skills to clearly present analytical findings and business recommendations. Highly motivated, productive, and teamwork-oriented.

- Good project management skills (clear goal setting, well-organized, detailed planning, and ability for tight timeline deliverables).

- Machine learning is Must