
Global financial services firm
Data Scientist Associate - Bengaluru
J.P. Morgan is a leading global financial services firm, established over 200 years ago.
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $2.5 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small business, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world's most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com.
We have an exciting opportunity for you to advance your data science career and shape the future of AI-driven solutions.
As a Data Scientist Associate within the Home Lending Originations Data and Analytics Team, you will collaborate with cross-functional teams to construct predictive models and develop robust RAG pipelines. You will extract valuable insights from complex datasets, drive data-driven decision-making, and deliver innovative AI solutions that enhance technology and business efficiency.
Responsibilities:
- Design, develop, and deploy classical ML models (Classification & Regression) and GenAI solutions (LLMs, RAG, prompt engineering), and Agentic AI workflows
- Design, develop, and manage prompt-based models on Large Language Models for financial services tasks
- Architect and oversee the development of next-generation machine learning models and systems using advanced technologies
- Align machine learning problem definition with business objectives to address real-world needs
- Drive innovation in machine learning solutions with a focus on scalability and flexibility
- Promote software and model quality, integrity, and security across the organization
- Architect and implement scalable AI Agents, Agentic Workflows, and GenAI applications for enterprise deployment
- Integrate GenAI solutions with enterprise platforms using API-based methods
Role Description:
Data Scientist required for Home Lending Data & Analytics, supporting key strategic business priorities across HL Origination & Servicing
- 4+ years of AI/ML experience in Classical ML, Generative AI, and Agentic AI
- Hands-on experience building best-in-class supervised & unsupervised ML models
- Strong knowledge of ML algorithms
- Logistic Regression, XGBoost, Random Forest, Gradient Boosting, K-Means, PCA, Anomaly Detection, etc.
- Experience with LLMs, prompt engineering, fine-tuning, RAG, and orchestration frameworks (Lang Chain, Llama Index)
- Familiarity with Agentic AI - multi-agent orchestration, tool-use agents, and frameworks like Lang Graph, CrewAI, Auto Gen
- Strong Python & SQL skills with proficiency in ML/AI libraries (scikit-learn, Py Torch/Tensor Flow, Hugging Face)
- Experience with MLOps (MLflow, Kubeflow) and cloud platforms (AWS/Azure/GCP) for model deployment
ABOUT US
JPMorgan Chase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
ABOUT THE TEAM
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.
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About JPMorgan Chase

JPMorgan Chase
PublicJPMorgan Chase & Co. is an American multinational banking institution headquartered in New York City and incorporated in Delaware. It is the largest bank in the United States, and the world's largest bank by market capitalization as of 2025.
300,000+
Employees
New York City
Headquarters
$500B
Valuation
Reviews
10 reviews
3.8
10 reviews
Work-life balance
3.5
Compensation
4.0
Culture
3.8
Career
3.2
Management
2.8
68%
Recommend to a friend
Pros
Good benefits and compensation
Supportive colleagues and environment
Flexible work arrangements
Cons
Long hours and heavy workload
Management issues and lack of direction
High stress and expectations
Salary Ranges
44 data points
Mid/L4
Senior/L5
Mid/L4 · Applied AI ML Associate
2 reports
$188,500
total per year
Base
$145,000
Stock
-
Bonus
-
$182,000
$195,000
Interview experience
4 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer rate
50%
Experience
Positive 25%
Neutral 75%
Negative 0%
Interview process
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
In-person/Final Interview
5
Offer
Common questions
Behavioral/STAR
Past Experience
Culture Fit
Financial Knowledge
Case Study
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