Data Science Manager in Talent cloud India Solutions
Job Description
Thrissur, Kerala
12 days ago Full–time
Job description
Job Purpose:
The Data Science Engineer will be responsible for leveraging advanced analytics, machine learning models, and data-driven insights to enhance credit card business performance. The role involves building predictive models, optimizing customer segmentation, and defining data-driven strategies to improve acquisition, usage, and retention.
Key Responsibilities:
Data Engineering & Model Development:
Develop and deploy machine learning models to optimize credit card acquisition, customer segmentation, and portfolio performance. Build predictive analytics frameworks for spend behavior, credit utilization, and delinquency risk. Engineer and maintain scalable data pipelines for real-time and batch processing. Optimize data storage, retrieval, and processing using cloud-based data platforms. Ensure data integrity, accuracy, and consistency for analytics-driven decision-making.
Business Enhancement & Strategy Definition:
Identify key business opportunities through data analysis and AI-driven insights. Develop data-driven strategies for customer retention, cross-sell, and upsell initiatives. Leverage advanced analytics to optimize credit limits, rewards programs, and campaign effectiveness. Provide actionable recommendations to improve customer lifecycle management. Collaborate with business teams to define KPIs and build dashboards for performance tracking.
Customer Analytics & Personalization:
Utilize AI and machine learning to enhance customer personalization across digital channels. Develop recommendation engines for customized offers, rewards, and spending insights. Implement real-time analytics for fraud detection and risk mitigation. Conduct deep-dive analysis on customer behavior and market trends to refine targeting.
Stakeholder Collaboration:
Work closely with Product, Marketing, Risk, and IT teams to implement data-driven solutions. Collaborate with compliance and regulatory teams to ensure data usage aligns with industry guidelines. Support decision-making by providing data-backed insights and reports to leadership. Work with external data providers and fintech partners to enhance analytical capabilities.
Innovation & Continuous Improvement:
Stay updated with the latest advancements in data science, AI, and machine learning. Develop automation frameworks for data analytics, campaign measurement, and performance optimization. Explore alternative data sources and AI-based techniques to improve predictive accuracy. Drive innovation in credit card analytics by implementing next-gen AI/ML techniques.
Key Skills and Competencies:
Proficiency in Python, SQL, R, and big data technologies (e.g., Spark, Hadoop). Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn). Strong expertise in data engineering, analytics, and cloud platforms (AWS, GCP, Azure). Knowledge of credit card business models, customer segmentation, and risk analytics. Hands-on experience in building real-time and batch processing data pipelines. Strong problem-solving, communication, and stakeholder management skills.
Educational and Experience Requirements:
Bachelor’s/Master’s degree in Data Science, Computer Science, Statistics, or a related field. 4-8 years of experience in data science, machine learning, and analytics, preferably in BFSI or fintech. Experience in credit card analytics, customer insights, and business strategy definition.
Thrissur, Kerala
