Designation: Senior Analyst - Data Science
Level: L2
Experience: 3 to 8 Years
Location: Chennai
Job Description:
We are seeking an Senior Analyst – Data Science to develop fraud prediction models using machine learning. The role involves contributing to the development and deployment of machine learning models and data-driven solutions to detect suspicious activity, mitigate financial crime, and ensure compliance. The ideal candidate will combine strong technical expertise with a solid understanding of machine learning and experience in development of end-to-end model development lifecycle.
Responsibilities:
- Assist in designing, developing, and deploying machine learning models for fraud prevention.
- Perform data analysis, feature engineering, and statistical modeling on large-scale transactional datasets.
- Collaborate with compliance, risk, and operations teams to translate requirements into actionable data science solutions.
- Build and maintain data pipelines using SQL, Python, and AWS services (SageMaker, Redshift, S3, Lambda).
- Support the integration of ML models into production environments, including Feedzai.
- Monitor and evaluate model performance, prepare reports, and recommend improvements.
- Ensure solutions align with regulatory standards and organizational policies.
- Provide guidance and mentorship to junior analysts where required.
Required Skillsets:
- Education: Bachelor’s/master’s degree in data science, Computer Science, Statistics, Applied Mathematics, or a related field.
- Experience: 3-8 years of experience in Data Science, with at least 2+ years in FinTech, Payments, Banking.
- Strong programming and analytical skills with Python, SQL, and statistical techniques.
- Experience in applying machine learning methods such as classification, clustering, anomaly detection, and NLP.
- Hands-on experience in AWS cloud services (SageMaker, S3).
- Exposure to Feedzai or similar fraud detection platforms preferred.
- Strong communication and collaboration skills, with the ability to work across cross-functional teams.
