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Corporate - Intelligent Solutions and Finance, Data Science / Quantitative Methods - Associate

Req #: 170108462
Location: New York, NY, US
Job Category: Accounting/Finance/Audit/Risk
Potential Referral Amount: 3000 US Dollar (USD)

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 http://www.jpmorganchase.com/.



F3 Labs is a joint venture between JP Morgan Intelligent Solutions (JPMIS) and Global Finance & Business Management (GF&BM). Global Finance & Business Management (GF&BM) mission is to ensure the company is capable of navigating all types of market environments while maintaining a fortress balance sheet. Intelligent Solutions (JPMIS) specializes in transforming JPMorgan Chase data assets into actionable analytics, insights and technologies that provide measurable business value for partners throughout JPMC.

 

The Lab’s work has historically revolved around the design and implementation of F3, the Firmwide Forecasting Framework – JPMC’s federated, end-to-end, multi-purpose forecasting platform.  In 2017, the Lab is shifting priorities to focus on incorporating advanced analytical tooling into F3.  Key lines of work include:

  • Automated analysis of forecast model output – which includes generation of automated benchmark forecasts, intelligent forecast comparisons, detection of potential anomalies of champion models with respect to benchmarks, and explanation of drivers of forecast misses and changes
  • Fast, interactive, assessment of the  impact of macroeconomic shocks on balance sheet, income statement, capital ratios, and other key metrics
  • Development of solutions  to easily understand the impact of changes in Firm’s strategy, originations, products under different economic scenarios through automated design of experiments
  • Extending  forecasting engines for Pricing, Valuation, and Optimization
  • Advanced ‘what if’ analyses and assessment of forecast uncertainty
  • Development of models for leading indicators to call cycle turns and plan through the Economic Cycle
  • Leveraging data assets for  knowledge discovery in data

We are searching for curious problem solvers to work in our next generation of forecasting and analytical tooling, with skills in one of the following areas, and willingness to learn a minimum of the other ones:

  • Statistics, Machine Learning and Data Science
  • Economics, Econometrics
  • Quantitative Development, System Architecture
  • Data Visualization, Analytical Applications, UI/UX

We offer an open, startup-like, dynamic and collaborative environment where you’ll have the opportunity to contribute initiatives that are transforming the industry, have ownership of entire workstreams and high visibility to senior management.


  • Strong analytical and problem solving, and more importantly, problem finding abilities
  • A curious mind and a healthy habit to dig deep in the questions to understand the context
  • A demonstrated ability to frame hard, open ended questions, and find creative solutions for them
  • Excellent quantitative skills, and expertise in one of the areas listed above
  • Excellent programming skills in R and Python for data science / scientific computing. C++ a plus
  • An advanced degree (preferably PhD or equivalent level of knowledge) in a quantitative field (e.g. computer science, finance, economics, electrical engineering, statistics, etc
  • In addition, our VP-level hires have at least three years of industry experience and a proven track record in a related position.
 

Our ideal hires with specialization in statistics / machine learning / data science also have:

 
  • Strong knowledge of data engineering – including databases (both relational and not relational), data I/O, cleansing, and transformation.  Knowledge of typical ‘big data’ technologies and data science stacks – (e.g. Hadoop, Spark, Storm, Kafka, Impala) a big plus.
  • Knowledge of typical Machine Learning stacks in R and Python, as well as deep learning frameworks (e.g. tensorflow, mxnet, torch etc)
  • A strong understanding of the different methods – at the very minimum at the level of “intelligent user” of packaged methods, but ideally also knowing the algorithmic details at the level of being able to modify existing learning methods and even write new ones from scratch
  • Empirical rigor, and a deeply internalized sense of the scientific method, having zero tolerance for bad science or improperly substantiated claims
 

Our ideal hires with specialization in economics / econometrics have …

 
  • Experience in developing or reviewing financial industry risk models
  • Excellent grasp of time series analysis, and modeling longitudinal data
  • Keen ability to interpret and diagnose models, understand sensitivities, and determine if models make economic sense
 

Our ideal hires with specialization in Quantitative Development and System Architecture have …

 
  • A thorough understanding of software engineering and agile development methodologies
  • Deep knowledge of Python or R internals, and traditional stacks for scientific computing (e.g. numpy, numba, mpi, cython, etc)
  • The ability to conceptualize abstract system designs, define interfaces, interact and give direction to technology teams responsible for the implementation
  • Ideally, experience with JP Morgan’s internal quantitative development frameworks (e.g. Athena) or big data stack (e.g. Spark)
 

Our ideal hires with specialization in Data Visualization / Analytical Applications / UI/UX have …

  • Knowledge of common web visualization toolkits (e.g. D3.js) and application frameworks (e.g. R’s Shiny, Angular, Polymer etc)
  • Knowledge and experience of reactive programming and the design patterns used in highly interactive web user interface environments
  • A deep appreciation of aesthetics, ergonomy, and the importance of user-centric design
 

Note: work location will move to our Hudson Yards office in January 2018


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