About the role
As a Senior Data Scientist at Hudson Data, you will design, build, and deploy the predictive models at the core of our products — credit risk, fraud detection, and customer decisioning models used by lenders and fintech partners. You will own models end to end: framing the problem, engineering features from large structured and unstructured datasets, training and validating models, putting them into production, and monitoring how they perform. You will work closely with engineering, product, and client teams, and help raise the modeling standards of the wider data science team. This is a full-time, onsite role in Gurugram, India. Responsibilities
• Build, validate, and deploy machine learning models (e.g. probability of default, first-payment default, fraud and never-pay detection, propensity, and segmentation models) from problem framing through production.
• Engineer features from large, messy datasets, including bureau, transactional, application, device, and alternative data.
• Choose the right approach for each problem, from GLMs and scorecards to gradient boosting (XGBoost/LightGBM), neural networks, and time-series methods, and justify the choice with evidence.
• Design robust validation: out-of-time and out-of-sample testing, cross-validation, reject inference, stability (PSI/CSI) checks, and bias and fairness assessment.
• Turn model outputs into business decisions: cut-off strategies, rules, and policies that balance approval rate, losses, and fraud capture.
• Partner with data engineering to productionize models and build scalable, reproducible training and scoring pipelines.
• Monitor models in production, detect drift and degradation, and lead recalibration and redevelopment.




• Write clear model documentation and present results to technical and non-technical audiences, including clients and senior leadership.
• Mentor junior data scientists and analysts, review their work, and set best practices for modeling, experimentation, and code quality.
• Keep up with new ML/AI techniques and bring the useful ones into our modeling stack. Required qualifications
• 5+ years of hands-on experience building and deploying predictive models in production.
• Solid command of statistical modeling and machine learning: GLM/logistic regression, Random Forest, GBM, neural networks, and time series.
• Expert Python (pandas, scikit-learn, XGBoost/LightGBM, TensorFlow or PyTorch) and strong SQL.
• Experience with big data tools such as BigQuery, Spark, Hive, or SQL Server.
• Deep understanding of model validation, performance metrics (AUC/Gini, KS, lift, precision/recall), and model risk.
• Proven ability to bring domain knowledge (financial risk, fraud, customer journey, marketing) into ML solutions.
• Ability to own problems end to end with minimal supervision and to explain complex results simply. Preferred qualifications
• Master's degree or PhD in computer science, statistics, mathematics, or a related field.
• Experience in fintech, lending, credit risk, fraud, or insurance.
• Experience with MLOps tooling (model registries, feature stores, CI/CD for models) and cloud platforms (GCP/AWS).
• Experience with H2O, graph-based fraud detection, or working with unstructured/text data.
• Experience mentoring or leading a small team of data scientists.

How to apply
Apply on our careers site: https://career.hudsondata.com/careers/data-scientist-1002

📌 Senior Data Scientist (Gurugram)
🏢 Hudson Data
📍 Gurugram