Data Scientist - BFSI Domain

Role Overview:

We are looking for a Data Scientist with experience in the BFSI domain, particularly in credit cards and marketing analytics. The ideal candidate will leverage advanced analytics, machine learning, and statistical modeling to optimize customer acquisition, campaign effectiveness, portfolio growth, customer engagement, and profitability. This role requires close collaboration with business, marketing, product, and risk teams to deliver data-driven solutions.

Key Responsibilities:

• Develop predictive models for customer acquisition, response propensity, cross-sell, upsell, and customer lifetime value.
• Build machine learning models for credit card marketing campaigns, customer segmentation, churn prediction, and offer optimization.
• Analyze campaign performance across digital, branch, direct sales, partner, and mixed marketing channels.
• Design and evaluate A/B tests and uplift models to measure campaign effectiveness.
• Create customer segmentation using clustering and behavioral analytics.
• Collaborate with marketing teams to improve campaign targeting and maximize ROI.
• Work with large structured and unstructured datasets from banking and customer touchpoints.
• Develop dashboards and automated reporting for campaign and portfolio performance.
• Partner with risk, fraud, and product teams to align analytics with business objectives.
• Present actionable insights to senior stakeholders and business leaders.

Required Skills:

• Strong knowledge of machine learning, statistics, and predictive analytics.
• Experience in BFSI, especially credit cards, retail banking, or lending.
• Hands-on experience in marketing analytics, campaign optimization, and customer segmentation.
• Proficiency in Python or R, SQL, and data visualization tools such as Power BI or Tableau.
• Experience with cloud platforms (AWS, Azure, or GCP) is preferred.
• Knowledge of A/B testing, uplift modeling, recommendation systems, and customer propensity modeling.
• Familiarity with big data technologies such as Spark or Hadoop is an advantage.
• Strong communication and stakeholder management skills.

Qualifications:

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related field.
• PhD is an added advantage.

Preferred Experience:

• Experience with credit card acquisition and portfolio analytics.
• Knowledge of customer lifecycle management and campaign management platforms.
• Exposure to CRM analytics and digital marketing analytics.
• Experience with marketing automation tools such as Adobe Campaign, Salesforce Marketing Cloud, SAS Campaign Management, or similar platforms.