Vice President- Applied AI/ML Scientist

Credence HR Services; Bengaluru; On-site; INR 1,800,000 - 2,500,000; Full time

Job summary

A financial services company in Bengaluru is seeking a Senior Applied AI/ML Scientist to design and implement machine learning models for fraud prevention and digital payments security. The role requires a Master's degree, over 10 years of experience in predictive modeling within financial institutions, and proficiency in Python, SQL, and AWS. This high-impact position involves mentoring junior scientists and driving technical strategy. Join us to make real-time financial decisions that substantially reduce fraud losses.

Qualifications

• 10+ years of experience in financial institutions.
• Proven ability to take models from research to production.
• Experience mentoring junior scientists.

Responsibilities

• Design and deploy machine learning models for fraud prevention.
• Implement advanced architectures like Graph Networks.
• Mentor junior team members.

Skills

Machine learning theory

Python programming

SQL

PySpark

AWS environments

Fraud prevention

Data pipelines

Mentoring

Education

Master's degree in a quantitative field

Tools

PyTorch

TensorFlow

XGBoost

Scikit-learn

Job description

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 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