JP Morgan Chase - Risk Associate - Machine Learning Model - Consumer Lending Business

Quantitative modeling is responsible for the development, maintenance and management of quantitative models that are used for most critical decisions within CCB Risk. With models that are aligned to line of business- Cards, Business Banking, Auto, Home Lending as well as for horizontal areas like fraud management, capital models, stress testing, CCAR etc. Quant Modelers regularly interact with variety of stakeholders including but not limited to LOB teams, MRGR, Fair Lending, Legal, Implementation,Tech teams etc. This an excellent opportunity in our Decision Sciences modeling team for an individual who thrive in a fast-paced and team-oriented environment where strong analytical skills, business acumen, and superior communication skills are leveraged.

Primary responsibility:

- Provide thought leadership and the needed quantitative expertise to deliver risk models.

- Liasoning with risk development partners like MRGR, Fair Lending, Legal, Technology and LOB Business Stakeholders

- Own quality of models developed, assuring accurate and appropriate model development standards, and right implementation of models.

- Accountable for business impact and robustness of models delivered.

- Handle a variety of modeling projects required dealing with different stakeholders, different statistical methods, and members across locations.

- Developing relationships with stakeholders to ensure that business problems can be discussed openly and helping envision where a model night be required

- Responsible for effectively developing the team

- Participate in external department projects which provide leadership and coaching.

- Decision making is both strategic and tactical in nature.

- Makes autonomous decisions on functional goals that influence larger departmental goals. - Consults with Directors and Senior Leaders on decisions regarding broad organizational impact."

Qualifications :

- 4+ years- statistical model development/ Machine learning model development experience in a deeply quantitative role in the financial services industry or Fintechs dealing with advanced analytical or machine learning methods

- 4+ years- SAS experience; well versed in SAS/Base, SAS/STAT, SAS/Macro, and data-mining procedures. SAS Certification preferred. OR

- 2+ years- experience in Python, Spark, Hive, Scala, Big Data, Hadoop, Keras, Scikitlearn etc.

- Demonstrates leadership within the team in terms of attitude, initiative and inclusivity.

- Experience managing US stakeholders and mid-sized teams will be helpful.

- Ability to effectively present ideas and presentations to Executive Management.

- Able to effectively develop and mentor the team

- A Master's or Ph.D. Degree in a technical or quantitative field such as Statistics, Economics, Finance, Mathematics, Computer Science, Engineering from Top-Tier university like IIT, IIM, IISc, ISI, IGIDR, etc.

- Experience utilizing relational and distributed data tools dealing with structured and unstructured data. Example tools include Hive, DB2, Oracle, or Teradata.

- Experience in developing, implementing, and testing traditional and Machine Learning driven risk models within financial institutions with strong regulatory oversight and tight timelines.

- Ability to deliver high-quality results under tight deadlines and be comfortable with the manipulation, analysis, and summarization of large quantities of data.

- Ability to make contributions to the group's knowledge base by proposing new and creative ways for approaching analytic problems and project design.