Job Title: Data Scientist II-3
Job ID: R-247687
Location: Navi Mumbai, Maharashtra, India – 400708
Experience Required: 3–5 Years
Education: Bachelor’s or Master’s in Computer Science / IT / Engineering / Mathematics / Statistics
Service Line: Software Engineering
Job Type: Full-time
Role Overview
Mastercard’s Finicity unit is seeking a highly skilled Data Scientist II to contribute to the Open Banking Initiative and enhance customer financial health through data-driven insights and machine learning. The role requires strong technical proficiency in building ML and DL models for applications like transaction classification, temporal analysis, and risk modeling using structured and unstructured data.
Key Responsibilities
Manipulate large datasets and apply statistical techniques like regression, clustering, LDA, segmentation, etc.
Design and implement ML models using SVM, XGBoost, LightGBM, CatBoost, Random Forest, etc.
Apply deep learning methods including LSTM, RNN, and Transformer models.
Build scalable ML pipelines and deploy models for financial risk and verification applications.
Measure, validate, and monitor machine learning model performance.
Present technical findings and strategic insights to both internal and client-facing audiences.
Innovate and propose creative solutions to novel problems in finance and data science.
Follow best practices in model development, versioning, and deployment.
Collaborate with cross-functional teams to align technical delivery with business goals.
Contribute to roadmap planning and identify resource gaps proactively.
Technical Requirements
3–5 years of experience in Data Science or ML model development.
Strong hands-on experience with Python, Pandas, Scikit-learn, TensorFlow, or similar frameworks.
Deep understanding of NLP, statistical modeling, and ML techniques.
Proficiency in SQL and experience working with databases.
Familiarity with Docker, Kubernetes, Containers, REST APIs, and event-driven architectures.
Experience building models on financial transaction data is a plus.
Knowledge of annotation techniques and token-based text analysis is preferred.
Understanding of model deployment, CI/CD pipelines, and monitoring strategies.
Exposure to credit risk and fraud analytics models is desirable.
Preferred Skills
Experience in FinTech or financial services domains.
Exposure to financial text data and anomaly detection.
Experience with model explainability frameworks.
Knowledge of data privacy and regulatory compliance in financial data science.
Strong verbal and written communication to convey complex insights clearly.
