Tonik Financial India

Roles & responsibilities: : The candidate must be able to independently manage his/ her own workstream and effectively collaborate with other regional teams. Develop and deploy machine learning models to support key business areas such as Credit Risk, Fraud Detection, Customer Segmentation, Marketing Optimization, and Collections Strategy. Collaborate with cross-functional teams (Data Engineers, Product Managers, Engineers) across Chennai, Manila, and Singapore to deliver production-grade ML solutions aligned with business goals. End-to-End Ownership: Drive the full lifecycle of ML solutionsfrom data exploration, feature engineering, and algorithm selection to deployment and performance monitoring. Build scalable data pipelines and model inference workflows (real-time and batch) to integrate predictive solutions into core banking and customer-facing platforms. Ensure model governance by adhering to regulatory and compliance standards in financial services environments. Preferred candidate profile: 1. Bachelors or Masters Degree in computer science/ Statistics/ Data Science/ Engineering 2. 8 + years of hands-on experience in data science, with a focus on applying machine learning in banking or fintech domains 3. Strong programming skills in Python, SQL , and experience with tools such as scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch 4. Experience in building credit risk models for Retail Banks, B2C FinTechs, NBFCs, System Integrators, SaaS-based Banking Platforms , or Product-led Financial Services companies is highly desirable. 5. Experience with cloud platforms (e.g., GCP, AWS, or Azure) and ML pipelines in production environments 6. Familiarity with real-time data processing and orchestration tools such as Kafka, Airflow, or Big Query 7. Above all, I must be a great team player and proactive communicator. This is a Table Stake Criteria!!!