Data Scientist Associate Senior

Testing Site - JPMC; Bengaluru; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

JPMorgan Chase in Bengaluru seeks an experienced Data Scientist Associate Senior to partner with business teams and deliver ML-driven software solutions. You will research, experiment, and productionize high-quality models and scalable data pipelines to generate actionable insights and optimize outcomes.

You will design and implement prompt-based models, apply prompt engineering, and build tools for training and evaluation while communicating results to stakeholders.

Qualifications

• Formal training or certification in data science with 3+ years of applied experience.
• Proven experience in prompt design or chatbot application development.
• Strong Python programming skills with ML frameworks (PyTorch or TensorFlow).
• Experience building data pipelines and API integration for NLP/LLMs.
• Hands-on cloud experience (AWS or Azure) for deployment and data processing.

Responsibilities

• Designs, deploys, and manages prompt-based models for NLP in financial services.
• Advances prompt engineering using LLM orchestration and agentic AI libraries.
• Collaborates with cross-functional teams to meet business needs.
• Communicates technical results clearly to stakeholders and leadership.
• Builds robust data pipelines and scalable data processing workflows.
• Develops tools/frameworks for prompt training, evaluation, and optimization.
• Analyzes data to assess model performance and opportunities for improvement.

Skills

Python programming

PyTorch

TensorFlow

Data pipelines

APIs

Cloud platforms

GIT

LLM orchestration

MLOps

Education

Data science certification or formal training

3+ years applied data science experience

Tools

PyTorch

TensorFlow

AWS

Azure

APIs

LLM orchestration libraries

GIT

Job description

Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.

As a Data Scientist Associate Senior at JPMorgan Chase within the Asset & Wealth Management, you will partner with various lines of business and functional teams to deliver innovative software solutions. You will have the opportunity to research, experiment, develop, and productionize high-quality machine learning models, services, and platforms that create significant business value. Additionally, you will design and implement scalable, reliable data processing pipelines and generate actionable insights to optimize business outcomes.

Job responsibilities

• Designs, deployment, and management of prompt-based models leveraging Large Language Models (LLMs) for diverse NLP tasks in financial services.
• Drives research and application of prompt engineering techniques to enhance model performance, utilizing LLM orchestration and agentic AI libraries.
• Collaborates with cross-functional teams to gather requirements and develop solutions that address organizational business needs.
• Communicates complex technical concepts and results effectively to both technical and non-technical stakeholders.
• Builds and maintain robust data pipelines and processing workflows for prompt engineering on LLMs, leveraging cloud services for scalability and efficiency.
• Develops and maintain tools and frameworks for prompt-based model training, evaluation, and optimization.
• Analyzes and interpret data to assess model performance and identify opportunities for improvement.

Required qualifications, capabilities, and skills

• Formal training or certification ondata science concepts and 3+ years applied experience
• Proven experience in prompt design and implementation, or chatbot application development.
• Strong programming skills in Python, with expertise in PyTorch or TensorFlow.
• Experience building data pipelines for both structured and unstructured data. Proficiency in developing APIs and integrating NLP or LLM models into software applications.
• Hands-on experience with cloud platforms (AWS or Azure) for AI/ML deployment and data processing.
• Excellent problem-solving skills and the ability to communicate ideas and results clearly to stakeholders and leadership.
• Working knowledge of deployment processes, including experience with GIT and version control systems.
• Familiarity with LLM orchestration and agentic AI libraries.
• Practical experience with MLOps tools and practices to ensure seamless integration of machine learning models into production environments.

Preferred qualifications, capabilities, and skills

• Familiarity with model fine-tuning techniques such as DPO (Direct Preference Optimization) and RLHF (Reinforcement Learning from Human Feedback).
• Knowledge of Java and Spark.