Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Mid-level ML role in Bangalore, popular Data Scientist title and metro location increase candidate competition.
Graph-centric fraud, risk and fintech focus makes industry-specific experience highly preferred over generic data backgrounds.
Explicit 4–7 years requirement plus production ML, cloud, and data skills enforce moderately strict filters.
Build and extend graph-native models (GNNs, embeddings, and custom graph algorithms) to detect fraud, collusion, and identity risk in banking and e-commerce networks.
Design, deploy, and maintain production-grade statistical, AI/ML, and deep learning models for fraud and risk, including real-time serving.
Run experiments and maintain data pipelines to fine-tune model performance and ship ML software with observability features.
Bachelor's, Master's, or PhD in ML, Computer Science, Math, Statistics, or related field.
4 to 7 years of experience in Data Science, AI, or ML Engineering roles.
Strong proficiency in Python, cloud platforms (AWS/Databricks/Azure), SQL, DBT, and Athena/BigQuery.
Experience shipping production ML models, ideally in fintech fraud, risk, payments, or compliance domains.
Experienced in graph modeling techniques for fraud and risk analytics.
Capable of working autonomously in ambiguous, unlabelled data environments to deliver business impact.
Demonstrates focus on building scalable, production-grade ML systems within fintech or related high-risk domains.