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Vice President- Applied AI/ML Scientist

Credence HR Services

5 - 10 years

Bengaluru

Posted: 07/03/2026

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Job Description

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? Were 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


  • Masters 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 PySpark
  • PyTorch or TensorFlow
  • 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

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