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Corporate - Strategic Forecasting Labs - Associate

Req #: 170125262
Location: Warsaw, MZ, PL
Job Category: Accounting/Finance/Audit/Risk
Potential Referral Amount: 0 Polish Zloty (PLN)
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 www.jpmorganchase.com.
 
Group Overview
The Strategic Forecasting Lab is an innovation accelerator under Global Finance and Business Management / Financial Analysis focused on advancing JPMC’s forecasting capabilities.   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, and in 2017, the Lab is shifting priorities to incorporating advanced analytical tooling into F3.  Current lines of work include:
  • Automated analysis of forecast model output – including generation of automated benchmark forecasts, intelligent forecast comparisons, detection of potential anomalies of champion models with respect to the benchmark, and explanation of drivers of forecast misses and changes
  • Real time, approximate 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
  • Development of models for leading indicators to call cycle turns and plan through the Economic Cycle
  • Extending  forecasting engines for Pricing, Valuation, and Optimization
  • Advanced ‘what if’ analyses and assessment of forecast uncertainty
  • Leveraging data assets for  knowledge discovery in data
     
Job Summary
The candidate will work in the Research arm of the Lab, developing innovative quantitative solutions across all lines of work of the lab. 
 
The candidate must have strong technical skills in statistical modeling and scientific computing to contribute to the development of core components of the platform, as well as excellent communication skills to present results.  The candidate will largely act as a domain expert, but hands-on involvement in prototyping different solutions is expected.
 
Key Responsibilities:
  • Research quantitative methods and approaches to solving problems in the lines of work of the lab, prototyping solutions, and partnering with development teams and technology for their implementation.
  • Deeply understand current forecasting models and the way they are used for analysis, identifying opportunities for improvement of the existing process– with particular emphasis in the introduction of new quantitative methods rooted in machine learning.
  • Document innovations for intellectual property filing and model review, where applicable. Prepare plans, status, and findings for management and regulators.
  • Participate in hands-on review of tools, documentation, process, and data to assess business requirements and conceptual and financial soundness of the implementations, as well as compliance with rules and best practices.
  • Stay current with emerging developments in models, approaches and requirements, both regulatory and others, and oversee the corresponding changes in models, systems, and processes.
  • Partner with internal and/or external Project Management Office resources to enhance end-to-end forecasting process and achieve continuous improvement.
Qualifications:
  • Excellent programming skills, preferably with experience in advanced R, Python
  • Knowledge of Machine Learning and some typical stacks for machine learning (e.g. scalable implementations of boosting, Tensorflow, MXNet, MLlib, Scikit-learn, tooling in R's MachineLearning task view), and/or model computational statistics and typical frameworks (e.g. implementations of GAM's and GAMLSS methods in R, Stan). 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
  • Knowledge of typical big data tooling, preferably with experience in Spark, Impala. Strong knowledge of data engineering – including databases (both relational and not relational), data I/O, cleansing, and transformation is highly desired, including advanced SQL analytical extensions for longitudinal data
  • Knowledge of Econometrics (Time Series Analysis, Longitudinal Data Analysis) desirable
  • Polished communications and Data Visualization highly desirable.  Familiarity with patterns and typical libraries (e.g. D3.js, Material) and application frameworks (e.g. R’s Shiny, Angular, Polymer etc.) commonly used to build highly interactive analytical applications
  • A balanced blend of pragmatism and solid theoretical grounds (yes, we do believe Ali Rahimi is mostly right, but at the same time, also understand that mankind have been building ships before hydrodynamics had been fully understood). Empirical rigor, and a deeply internalized sense of the scientific method, having zero tolerance for bad science or improperly substantiated claims
  • An inquisitive mind with a healthy habit to dig deep in the questions to understand the context, ask hard questions, and reframe problems when needed
  • Strong analytical and problem solving, and more importantly, problem finding abilities
  • An advanced degree (preferably PhD or equivalent level of knowledge) in a quantitative field (e.g. computer science, finance, economics, electrical engineering, statistics, etc.)
About J.P. Morgan’s Corporate & Investment Bank
 
J.P. Morgan’s Corporate & Investment Bank is a global leader across banking, markets and investor services. The world’s most important corporations, governments and institutions entrust us with their business in more than 100 countries. With $18 trillion of assets under custody and $393 billion in deposits, the Corporate & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.  Further information about J.P. Morgan is available at www.jpmorgan.com
JPMorgan Chase & Co. offers an exceptional benefits program and a highly competitive compensation package. JPMorgan Chase & Co. is an Equal Opportunity Employer.
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