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JPMorganChase

Quant Modelling - Vice President

Job Posted 4 Days Ago Posted 4 Days Ago
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Hybrid
Bengaluru, Karnataka
Senior level
Hybrid
Bengaluru, Karnataka
Senior level
Lead the MRGR Data Science Group, managing model risk management activities, ensuring robust model development practices, and communicating risk assessments.
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Job Description
As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class.
MRGR is a global team of modeling experts within the firm's Risk Management and Compliance organization. The team is responsible for conducting independent model validation and model governance activities to help identify, measure, and mitigate Model Risk in the firm. The objective is to ensure that models are fit for purpose, used appropriately within the business context for which have been approved, and that model users are aware of the model limitations and how they could impact business decisions.
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


About Us
JPMorganChase, 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 professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.

Top Skills

Deep Learning
Gans
Keras
Large Language Models
Machine Learning
Nlp
Numpy
Ocr
Pandas
Python
PyTorch
Reinforcement Learning
Scikit-Learn
Scipy
TensorFlow
Transformers
Xgboost

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