Job Description

An exciting opportunity to work in a small and strategically important Modernization team within the Global Research business. The Research Modernization team sits within the Corporate and Investment Bank Global Research organization and provides both internal and external clients with transformational digital products, experiences and solutions for the curation and consumption of our Global Research products across a variety of client channels. The Research Modernization team seeks out new opportunities and promotes execution and change across the organization.

As a Data Engineer in the Global Research Modernization team, you will bring dynamic energy, strong attention to detail, and the ability to multitask.

Job Responsibilities

• Build, deploy, and maintain business processes using Python.

• Collaborate with Research Analysts to understand their data needs and translate their requirements into data/information solutions.

• Utilize Python for data handling and manipulation to prepare and transform data into a usable format for Research Analysts, deriving meaningful insights from complex datasets to support data-driven decision making by Research Analysts.

• Develop scripts and tools to automate repetitive tasks, improve efficiency, and streamline workflows.

• Research and analyze datasets using a variety of analytical techniques in Python.

• Create, productionize, and store enhanced and original datasets; improve data analysis and discovery tools; model the data with a focus on ease of storage, retrieval, and usability.

• Automate publication and analytics workflows for Research Analysts.

• Monitor and troubleshoot process performance and reliability issues in a timely manner.

• Identify opportunities for process improvement and develop policies for data access and governance.

• Ensure data quality and integrity through effective validation and testing processes.

Required Qualifications, Capabilities, and Skills

• Bachelor’s degree in engineering, computer science, information technology, or other data science/analytics fields.

• 2+ years of hands-on experience in developing applications using Python.

• High level of proficiency in Python and relevant packages for data handling and manipulation. It is essential that the candidate has hands-on experience and in-depth knowledge of libraries like Pandas and NumPy.

• Strong background in data structures, algorithms, and data engineering, with experience in data and technology platforms.

• Strong analytical and problem-solving skills.

• Excellent communication, presentation, interpersonal, and organizational skills.

Preferred qualifications, capabilities, and skills

• Understanding of libraries for web scraping, such as BeautifulSoup and Selenium, will be a plus.

• Detail-oriented, with a highly disciplined approach to processes and controls.

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.