Principal Analyst - Applied AI
HybridBengaluru, Karnataka, India
Job Summary
Build and test solution components for data science, machine learning, and GenAI use cases by preparing data, developing features, and configuring prompts. Execute defined evaluation plans including performance testing, quality checks, and reproducibility verification while maintaining complete technical artifacts and documentation. Troubleshoot defects systematically, document assumptions, and contribute reusable code, test scripts, and lessons learned to improve team methods. Collaborate with the India delivery lead and U.S.-based senior practitioners to deliver practical, trusted AI solutions within a regulated financial environment.
Required Qualifications
- Bachelor's Degree and 4 years of experience in Data management, information technology, financial services, enterprise risk management, or related disciplines with hands-on AI/advanced analytics delivery
- High School Diploma or GED and 8 years of experience in Data management, information technology, financial services, enterprise risk management, or related disciplines with hands-on AI/advanced analytics delivery
- Hands-on academic project, internship, or professional experience in data science, machine learning, analytics engineering, NLP, or GenAI solution development — with evidence of building and testing real solutions, not just coursework
- Working proficiency in Python and SQL
- Exposure to common data science, machine learning, or GenAI libraries, notebook environments, and basic software development practices such as version control
- Understanding of data preparation, model evaluation, test design, documentation practices, and basic monitoring concepts
- Experience with enterprise data or cloud environments
- Genuine interest in both conventional AI/ML and GenAI methods — with the intellectual honesty to select and evaluate methods based on what the problem requires, not what is most novel
- Strong attention to detail, structured problem-solving approach, demonstrated willingness to learn and receive feedback, and the ability to collaborate effectively in a distributed global team
- Clear written communication: the ability to describe technical work, test outcomes, assumptions, and blockers in a way that is useful to colleagues who were not in the room when the work was done
- Python
- SQL
- Machine Learning Fundamentals
- Generative AI / LLMs
- Prompt Engineering
- RAG Concepts
- Data Analysis & Feature Engineering
- Git / Version Control
- Model Evaluation & Testing
Desired Qualifications
- Experience with enterprise data or cloud environments
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