JPMorgan Quant Modelling - Vice President 

India, Karnataka, Bengaluru 

647806114

Being part of the MRGR team will put you at the center of the firm’s model validation and governance activities with exposure to a wide variety of model types and cutting edge modeling techniques, while frequently interacting with the best and brightest in the firm. You will expand your knowledge of the different forecasting models used in the firm, their unique limitations, and use that knowledge to help shape business strategy and protect the firm.

The successful candidate will head the MRGR Data Science Group in Bangalore, managing a team of junior reviewers. This group will perform the following model risk management activities for Data Science models in the firm:

• Set standards for robust model development practices and enhance them as needed to meet evolving industry standards
• Evaluate adherence to development standards including soundness of model design, reasonableness of assumptions, reliability of inputs, completeness of testing, correctness of implementation, and suitability of performance metrics
• Identify weaknesses, limitations, and emerging risks through independent testing, building of benchmark models, and ongoing monitoring activities
• Communicate risk assessments and findings to stakeholders, and document in high quality technical reports
• Assist the firm in maintaining (i) appropriateness of ongoing model usage, and (ii) the level of aggregate model risk within risk appetite

Minimum Skills, Experience and Qualifications:

We are looking for someone excited to join our organization. If you meet the minimum requirements below, you are encouraged to apply to be considered for this role.

• A Ph.D. or Master’s degree in a Data Science oriented field such as Data Science, Computer Science or Statistics, is required
• 7+ years of experience in a quantitative modeling role, such as Data Science, Quantitative Model Development, Model Validation, or Technology focused on Data Science, including hands-on experience with building/testing Machine Learning models
• Domain expertise in following areas: Data Science, Machine Learning and Artificial Intelligence. Knowledge and experience in database interfacing and analysis of large data sets is a plus
• Strong understanding of Machine Learning / Data Science theory, techniques and tools including Transformers, Large Language Models, NLP, GANs, Deep Learning, OCR, XGBoost, and Reinforcement Learning
• Proven managerial experience or demonstrated leadership abilities, with a track record of successfully leading and managing quantitative teams
• Proficiency in Python programming, with experience in the Python machine learning library and ecosystem, including NumPy, SciPy, Scikit-learn, Pandas, TensorFlow, Keras, and PyTorch
• Understanding of the machine learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop
• Strong communication skills verbally and particularly in writing, with the ability to interface with other functional areas in the firm on model-related issues and write high quality technical reports
• Risk and control mindset: ability to ask incisive questions, assess materiality of model issues, and escalate issues appropriately