
Applied AI ML Lead, Vice President – Global Private Bank Ops and Core Tech
at J.P. Morgan
Posted 19 days ago
No clicks
- Compensation
- Not specified
- City
- Bengaluru
- Country
- India
Currency: Not specified
Senior Applied AI/ML role within Global Private Bank operations and core technology, focused on designing, developing and productionizing AI/ML solutions to enhance client experience, efficiency and reduce risk. The role involves stakeholder engagement, data wrangling, modeling (including NLP and LLMs), and deploying end-to-end solutions across teams. You'll drive R&D, coach AI/ML team members, and collaborate cross-functionally to align solutions with business needs. Strong Python and ML framework experience plus familiarity with Spark/Hive/SQL and financial services is desired.
Location: Bengaluru, Karnataka, India
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As an Applied AI/ML Vice President within Asset & Wealth Management, you will utilize your quantitative, data science, and analytical skills to tackle complex problems. Your role will involve collaborating with various teams to design, develop, evaluate, and execute data science and analytical solutions, all while maintaining a deep functional understanding of the business problem at hand. Your responsibilities will also include data wrangling, data analysis, and modeling, which encompasses model selection and the creation of swift, applicable modeling solutions.
Job responsibilities:
- Engages with stakeholders and understanding business requirements,
- Develops AI/ML solutions to address impactful business needs,
- Works with other team members to productionize end-to-end AI/ML solutions,
- Engages in research and development of innovative relevant solutions,
- Coaches other AI/ML team members towards both personal and professional success,
- Collaborates across teams to attain the mission and vision of the team and the firm
Required qualifications, capabilities and skills:
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- Advanced degree in analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis, Operations Research)
- Experience in the application of AI/ML to a relevant field.
- Demonstrated practical experience in machine learning techniques, supervised, unsupervised, and semi-supervised.
- Strong experience in natural language processing (NLP) and its applications.
- Solid coding level in Python, with experience in leveraging libraries, like Tensorflow, Keras, Pytorch, Scikit-learn, or others.
- Previous experience in working on Spark, Hive, or SQL.
Preferred Qualifications, capabilities and skills:
- Demonstrated practical experience in application of LLMs for solving business problems.
- Financial service background.
- PhD in one of the above disciplines.




