Data Science Lead

Job description

We ae looking for candidates with experience in machine learning, Data science and Credit card. We are looking for a highly skilled **Senior Data Scientist** with **58 years of experience** in **classical machine learning** and **data science**. The role focuses on building predictive models and analytical solutions for **credit card fraud detection, transaction monitoring, payment analytics, and credit risk modeling** within the digital payments and fintech ecosystem. **Key Responsibilities:** - Design and implement **predictive modeling solutions** for fraud detection, credit risk scoring, and customer segmentation. - Apply **classical ML algorithms** including logistic regression, decision trees, random forest, support vector machines (SVM), gradient boosting (XGBoost, LightGBM), clustering (K-means, hierarchical), and time series forecasting. - Develop and optimize **transaction monitoring systems** to detect anomalies and fraudulent activities. - Conduct **payment analytics** to improve customer experience and operational efficiency. - Collaborate with risk, compliance, and product teams to align ML solutions with business objectives. - Ensure models meet **regulatory compliance, explainability, and governance standards** in financial services. - Present actionable insights and recommendations to senior stakeholders using clear visualizations and reports. **Required Skills & Experience:** - **5–8 years** of professional experience in **data science / machine learning** roles. - Strong expertise in **classical ML techniques** (logistic regression, decision trees, random forest, SVM, gradient boosting, clustering, time series forecasting). - Proven experience in **credit card fraud detection, transaction monitoring, payment analytics, and credit risk modeling**. - Proficiency in **Python, R, SQL** and ML libraries (scikit-learn, XGBoost, LightGBM). - Experience with **large-scale financial datasets** and feature engineering. - Knowledge of **digital payments and fintech domain**. - Strong problem-solving, analytical, and communication skills. **Preferred Qualifications** - Exposure to **digital payment systems, fintech platforms, or RegTech solutions**. - Familiarity with **cloud platforms** (AWS, Azure, GCP) for ML deployment. - Advanced degree (M.Tech/M.S./Ph.D.) in Computer Science, Data Science, Statistics, or related field. - Experience in **model explainability, bias detection, and responsible AI practices**. **Why Join Us:** - Work on **high-impact ML projects** in the credit card and fintech industry. - Opportunity to lead initiatives in **fraud prevention, credit risk, and digital payment analytics**. - Collaborate with cross-functional teams in a fast-paced, innovation-driven environment. Competitive compensation, growth opportunities, and exposure to cutting-edge fintech solutions.