Data Scientist - Fraud & Analytics
Skills
About the role
This is an on-site Data Scientist role in Gurgaon/Gurugram for someone with 2–6 years of experience building fraud and risk models. You'll own machine learning work from feature engineering through deployment and monitoring, while supporting fraud analytics and reporting.
What you’ll do
- Build and deploy machine learning models for fraud detection and transaction risk.
- Manage model training, validation, deployment, monitoring, and feature engineering.
- Analyze fraud data and improve prevention rules and risk strategies.
- Turn analytical findings into operational policies with cross-functional teams.
- Support Power BI dashboards and fraud-risk reporting.
- Guide junior team members and lead analytics initiatives.
What they’re looking for
- Hands-on Python and machine learning experience.
- Experience with predictive modeling, MLOps, model deployment, data modeling, and SQL.
- Experience building, deploying, and maintaining end-to-end machine learning models.
- Availability to work from the office in Gurugram.
- Candidates should already be based in the job location because relocation is not offered.
- Early joiners are preferred, with a minimum two-week joining requirement.
- Candidates with up to 30 days of official notice period may be considered.
Nice to have
- Experience in fraud detection, financial risk, banking, fintech, or analytics.
- Exposure to AWS services such as S3, SageMaker, Lambda, or Glue.
- Experience with Git, CI/CD, and MLOps practices.
- Knowledge of Pandas, scikit-learn, XGBoost, TensorFlow, or PyTorch.
What’s on offer
- Work from the office in Gurgaon/Gurugram.
- No relocation cases are being considered.
Questions about this role
Where is this Data Scientist role based?
The role is based in Gurgaon/Gurugram and requires work from the office.
How much experience is required?
The posting asks for 2–6 years of experience.
Is relocation available?
No. The posting says only candidates already based in the job location will be considered.
What skills are required?
Python, machine learning, predictive modeling, MLOps, feature engineering, data modeling, and SQL are required.
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