Associate - Data Engineering

2 weeks ago

Mumbai, India Xcelyst Ltd Full time

Role : Associate - Data Engineering

As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. Quantitative Research (QR) is an expert quantitative modeling group in J.P. Morgan, as well as a leader in financial engineering, data analytics, statistical modeling and portfolio management. As a global team, QR partners with traders, marketers and risk managers across all products and regions, contributes to sales and client interaction, product innovation, valuation and risk management, inventory and portfolio optimization, electronic trading and market making, and appropriate financial risk controls. Description for Internal Candidates

Posting Description :

We are looking for an experienced Data Analyst to join our team in Mumbai, India. The Wholesale Credit Data QR team's mission is to design, analyze, deliver firm-wide Data to support the firm's Wholesale Credit Stress (CCAR, ICAAP, Risk Appetite) and Loan loss reserves models. In particular, for this role, the team focuses on Data model definition, evolution of Data Dictionary to enable deep dive Data Analysis and Analytical explorations. The successful candidate will work on the evolution of our frameworks, underlying Data platforms and related tools to enhance ease of integration of pricing and forecast models, improve flexibility and extendibility of the framework as well as improve scalability and performance. This will require the candidates to work with other more experienced Wholesale Credit model developers and business partners and enhance their quantitative as well as business skills.

Job Responsibilities

- You will work as data engineer, to create or build data pipeline, define API to source data from different systems, perform complex transformation or enhancements to data and optimize end to end run.

- To write business requirements in the form of JIRA epics & user stories to develop data and system requirements for credit risk modelling platform

- Perform data analysis to support model development and analytics

- Liaise with various lines of business and risk modelers, thoroughly understand various models for BASEL, CCAR, CECL and other credit risk models

- Work with multiple stakeholders to elicit, analyze, refine and document business process and data requirements

- Collaborate through the entire Software Development Life Cycle (SDLC) including planning, analysis and testing of new applications and enhancements to existing applications

- Perform user acceptance testing and deliver demos to stakeholders by SQL queries or Python scripts

Required qualifications, capabilities, and skills

- Bachelor's or Master's in Computer Science, Data Analytics or equivalent discipline.


- Experience of 4+ years in financial services, data analytics and similar.

- Data Analysis and data manipulation skills using SQL , Python, object orient programming & MS Excel is required.


- Strong analytical skills in forecasting and interpreting results and comfortable working with large quantities of data

- Experience on building data architecture to source data from different systems, handling complex transformation ad optimizing the end to end solution

- Ability to solve problems creatively while working in a dynamic and challenging environment under tight deadlines. Eagerness to learn about Credit Risk, Risk Parameters, Regulatory and Accounting concepts

- Detail oriented and strong organizational skills.


- Excellent communication abilities, both written and oral

- Experience implementing analytics frameworks in finance.


- Experience with source control, automated build/test systems, code coverage, unit testing and release processes

Preferred qualifications, capabilities, and skills

- Experience in software engineering to build data architecture based on python, object orient programming, SQL etc. is preferable

- Knowledge of Wholesale Credit, CCAR, Allowance (IFRS 9/CECL), Basel II/III regulatory capital

- Proven ability to develop collaborative relationships with key internal partners to achieve objectives and prioritizations

(ref:hirist.tech)

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