Posted 14 days ago
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As a Data Scientist Lead at JPMorgan Chase within Asset & Wealth Management, you will research, develop, and productionize machine learning and prompt-based LLM models and build scalable data processing pipelines. You will design, deploy, and maintain prompt engineering frameworks, integrate NLP/LLM models into applications, and leverage cloud platforms and MLOps tools for production. The role requires collaborating with cross-functional teams, communicating results to stakeholders, and improving model performance to drive business impact.
- Compensation
- Not specified
- City
- Mumbai
- Country
- India
Currency: Not specified
Full Job Description
Location: Mumbai, Maharashtra, India
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Data Scientist Lead at JPMorgan Chase within Asset and Wealth Management, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you will have opportunity to research, experiment, develop, and productionize high-quality machine learning models, services, and platforms to make a significant business impact. You will also design and implement highly scalable and reliable data processing pipelines and perform analysis and insights to promote and optimize business results.
Job responsibilities
- Designs, deploys and manages prompt-based models on LLMs for various NLP tasks in the financial services domain
- Conducts research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field, exploring and utilizing LLM orchestration and agentic AI libraries.
- Collaborates with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization
- Communicates effectively with both technical and non-technical stakeholders
- Builds and maintains data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.
- Develops and maintains tools and framework for prompt-based model training, evaluation and optimization
- Analyzes and interprets data to evaluate model performance to identify areas of improvement
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Experience with prompt design and implementation or chatbot application
- Strong programming skills in Python with experience in PyTorch or TensorFlow
- Experience building data pipelines for both structured and unstructured data processing.
- Experience 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 and the ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner
- Basic knowledge of deployment processes, including experience with GIT and version control systems
- Familiarity with LLM orchestration and agentic AI libraries
Hands on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environment
- Familiarity with model fine-tuning techniques such as DPO and RLHF.
- Knowledge of Java, Spark
- Knowledge of financial products and services including trading, investment and risk management
