Senior Analyst - Data Science
- Location Chennai, Tamil Nadu, India (CHN)
- Experience 1-8 yrs
- Job type Full-time
- Posted 6 Oct 2026
You will be taken to the employer’s own careers page to apply.
Job details
- Qualification
- PhD
- Job ID
- J_5801
Job description
Designation : Senior Analyst - Data Science Level : L2 Location : Chennai, Tamil Nadu , India Experience : 2 to 8 Years
Job Role : Education: PhD in Statistics, Data Science, Machine Learning, Deep Learning, or a related quantitative field. Research & Publication Mindset: Strong record or potential for publishing original research in top-tier machine learning conference proceedings or journals. Technical Expertise: Advanced domain knowledge in Graph Neural Networks (GNNs), Transformers, Variational Autoencoders (VAEs), and cutting-edge deep learning architectures. Programming & Tools: Expert-level mastery of Python, PyTorch/PyTorch Geometric (PyG), DGL, SQL, and core statistical modeling libraries. Industry Experience: 1+ years of post-PhD or industry experience in Data Science, with a preferred focus on FinTech, Payments, Banking, or Financial Crime. Soft Skills: Exceptional technical storytelling, cross-functional collaboration, and the ability to articulate complex mathematical concepts to business stakeholders.
Responsibilities
Cutting-Edge R&D: Design, develop, and benchmark state-of-the-art ML and Graph Neural Network (GNN) algorithms to uncover complex fraud networks and anti-money laundering (AML) patterns. End-to-End Delivery: Lead the complete lifecycle of advanced machine learning models—from problem formulation, data extraction, and feature engineering to production deployment and monitoring. Applied Innovation & Publications: Translate novel AI/ML research into production-grade enterprise solutions while identifying key breakthroughs for academic publication and IP creation. Scalable Data Architecture: Build, optimize, and maintain large-scale data and ML pipelines utilizing Python, SQL, and AWS infrastructure (SageMaker, Redshift, Lambda, S3). Platform Integration: Support the integration, real-time scoring, and evaluation of ML models into enterprise fraud detection platforms such as Feedzai. Performance & Compliance: Continuously monitor model drift and performance metrics, ensuring all deployed solutions comply strictly with financial regulatory and governance standards.