Senior Associate, Data Scientist Campaign Management

Position Summary
Data Scientist - Campaign Management

Responsible for leveraging data, analytics, and predictive modeling to improve Campaign effectiveness, Customer engagement, and Business Outcomes. The role supports campaign strategy development by Identifying Target customers, Generating Actionable Insights, and Optimizing Marketing Performance.

Key Responsibilities

Customer Analytics & Segmentation

1. Develop customer segmentation frameworks based on behavior, demographics, transaction patterns, and product holdings.
2. Identify optimal Campaign channels to maximize revenue and Customer Engagement
3. Analyze customer journeys and identify opportunities for Acquisition, Cross-Sell, Up-sell, Retention, and Reactivation Campaigns.
4. Generate actionable insights to support business and marketing strategies.

Campaign Planning & Execution

1. Manage end-to-end campaign execution across multiple products, channels, and  customer segments.
2. Translate business requirements into campaign logic, target criteria, and execution plans.
3. Prepare campaign schedules and coordinate campaign deployment timelines.
4. Ensure campaign activities are executed accurately and within agreed SLAs.

Predictive Modeling
1. Build and maintain predictive models such as:
Propensity-to-Buy
Propensity-to-Churn
Next Best Offer (NBO)
Customer Lifetime Value (CLV)
Response/Uplift Models
2. Continuously monitor model performance and recommend enhancements.

Education Preference
Bachelor Degrees in : Mathematics, Statistics, Data Science

Programming :
Python
SQL

Analytics & Machine Learning
Predictive modeling
Customer segmentation
Classification and regression models
Forecasting models
Recommendation engines
Model performance evaluation

Visualization Tools
Power BI
Tableau

Soft Skills
1. Good communication and stakeholder management skills.
2. Ability to manage multiple projects and deadlines.

Location:

Capital Place Branch

Job:

Analytics

Schedule:

Regular

Employee Status:

Full time