Corporate - Strategic Forecasting Labs, Data Science Associate

Job description

JPMorgan Chase & Co . (NYSE: JPM) is a leading global financial services firm with assets of $2.6 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/ .

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. 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 design and creation of the next generation analytical tooling for forecasting. Leveraging AI and Machine Learning techniques, the candidate will develop solutions for forecast analysis (e.g. isolating hot spots and anomalies, understanding the effect of assumptions, decomposing and explaining forecast error) and advanced what-if analyses, which will be used to support the risk, finance and strategic decisions across all the lines of business of the Firm.

The candidate must have strong technical skills in scientific and data computing. The role will involve developing data manipulation, modeling, statistical analysis and front end visualization solutions, so good command of typical data science toolchains is expected. Some level of hands-on involvement in the software development process and active contribution of reusable libraries for the platform are expected, so a deep understanding of systems architecture and good software engineering skills are required.

Core Responsibilities:

· Partner with Line of Business subject matter experts, Technology, Risk and Finance teams to understand current analyses performed, identify, an implement potential improvements
· Create analytical apps that can use the F3 data sets and provide advanced and interactive analytical insights using advanced statistical methods
· Identify opportunities for leveraging our data assets to produce insights

Desired profile

·  Strong analytical and problem solving abilities. Demonstrated ability to frame hard, open ended questions, and find creative solutions for them.
·  Excellent programming skills in R and Python for data science / scientific computing. C++ a plus.
·  Knowledge of data engineering – including databases (both relational and not relational), SQL language, 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.
·  Experience in developing or reviewing financial industry risk models a plus.
·  Knowledge of interactive visualization tooling such as Tableau, Qlik and Shiny. Strong analytical and problem solving abilities; ability to communicate results clearly both written and using infographics and visual explanations
·  Advanced degree in a quantitative field (e.g. computer science, finance, economics, electrical engineering, statistics, etc)