Vice President- Applied AI​/ML Scientist

Location: Bengaluru

Hiring:
Vice President - Applied AI/ML Scientist - Fraud & Risk Analytics

Are you passionate about building AI systems that make real-time decisions on live financial transactions? Do you thrive at the intersection of research and production? We’re looking for a  senior Applied AI/ML Scientist  to help shape the future of fraud prevention and digital payments security.
This is a  high-visibility, high-impact role  where your models will directly reduce fraud losses, influence firmwide strategy, and power a scalable fraud prevention platform used across the organization.

You will:

Design, train, and deploy advanced  machine learning models  for fraud prevention and risk management
Research and implement cutting-edge architectures, including :  Graph Networks, Agentic AI systems, Large Language Models (LLMs)
Build and rigorously test AI agents to ensure reliability, robustness, and real-world effectiveness
Develop scalable data pipelines and analytical tools using  Databricks, PySpark, and AWS
Monitor, optimize, and continuously evolve models to adapt to emerging fraud patterns
Drive technical strategy and influence the analytical direction of the team
Mentor junior scientists and promote engineering and modeling best practices
Partner cross-functionally with Product, Engineering, and Data teams to align AI solutions with business impact
Build reusable, production-grade ML frameworks that elevate firmwide fraud prevention capabilities

What You Bring

Master’s degree (or equivalent experience) in Computer Science, Statistics, Mathematics, Economics, or related quantitative field
10+ years of experience building and managing predictive risk models in financial institutions
Strong foundation in machine learning theory (not just library usage)
Hands-on experience with:
Python, SQL, and/or Py Spark
PyTorch or Tensor Flow
XGBoost, Scikit-learn, or similar classical ML tools
Experience working with large-scale datasets and distributed data processing
Experience in AWS cloud environments
Proven ability to take models from research → production → monitoring → optimization
Experience mentoring or coaching junior team members

Nice to Have

Experience or strong interest in Graph Analytics and Agentic AI
Knowledge of GSQL
Experience working with both structured and unstructured data
Product mindset — you understand that models are part of a broader user and business experience
Passion for impact — your models making real-time financial decisions energizes you