Job Description
Key Skills: Risk Analytics, Data Scientist, Fraud Analysis, Python, Machine Learning, SQL
nRoles and Responsibilities:
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- Develop fraud detection, anomaly detection, and risk scoring models for high-volume transaction and account activity.n
- Design feature engineering and validation approaches for structured, time-based, and relationship-driven fraud signals.n
- Build and maintain ETL/ELT pipelines that support model training, scoring, and analytics workflows.n
- Integrate REST APIs and external data sources into production analytics and decisioning processes.n
- Partner with engineering and risk teams to operationalize models, monitor outcomes, and improve model quality over time.n

nSkills Required:
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- 6-10 years of experience in data science, analytics engineering, machine learning, or a closely related discipline.n




- Advanced hands-on experience in Python and SQL for data science and analytics engineering work.n
- Robust background in fraud analysis, risk analytics, machine learning, and statistical modeling.n
- Experience with production-grade data pipelines, model validation, and model monitoring on large datasets.n
- Ability to support API integrations, CI/CD practices, and cloud-based analytical environments.n

nGood to Have:
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- Snowflake, PostgreSQL, Neo4j, Cypher, MLOps, Azure, AWS, Kubernetes, observability tools, and fraud case-management experience.n

nEducation: Bachelor's degree in data science, computer science, engineering, statistics, mathematics, operations research, or a related quantitative field; Master's degree preferred.

📌 Lead Data Scientist_102571 (Tamil Nadu)
🏢 MyCareernet
📍 Tamil Nadu