
Global financial services firm
Reference Data Analyst
Required skills
Python
Are you someone who is looking to enrich your experience in reference data by working on diverse securities and market data analytics?
As a Reference Data Analyst within the Reference Data Team, you will be responsible for the creation and maintenance of all types of securities (such as equity, fixed income, derivatives, etc.) and pricing. You will set up new issuers and entities in internal systems, provide index onboarding and maintenance, and offer operational support towards market data analytics. Your data-promoten mindset will be crucial to deliver solutions that meet the needs of stakeholders and our global business.
Job Responsibilities:
- Create and maintain all type of securities (such as equity, fixed income, derivatives etc.) and pricing, setting up new Issuers and entities in internal systems, index onboarding and maintenance and operational support towards market data analytics.
- Execute timely tasks and ad-hoc projects, stakeholder updates and timely escalation of issues and their resolution.
- Partner with Technology, Chief Data Office, and Operations teams to perform enhancement testing and implementation.
- Contribute towards designing and implementing controlled operational processes to meet specific business needs.
- Liaise with internal and external vendors to resolve issues, minimize risk and contribute to the success and overall execution of the strategic agenda items.
- Maintain high standards and follow operational controls to reduce financial, regulatory and reputations risks.
- Maintain operational and control metrics for senior management oversight.
- Identify automation opportunities and contribute to the design, testing, and deployment of scalable automation solutions in collaboration with transformation and technology partners.
Required Qualifications, Capabilities, and Skills:
- Bachelor’s degree in commerce or Master of Business Administration in finance
- Knowledge of industry activities, including instruments and pricing reference data, entity data, corporate actions, stock markets and all asset classes, along with index&
- benchmark and market data (including various funds and Environmental, Social and Governance-related firms).
- Depth knowledge of Intelligent Automation tools like Ui Path, Python, and Alteryx. Deploy/implement scalable solutions to streamline operations, enhance efficiency, and optimize workflows.
- Proficient in Microsoft Office.
- Analytical and problem-solving abilities with attention to detail.
- Self-motivated and proactive with the proven ability to work accurately and under pressure to meet deadlines.
- Demonstrate ability to effectively communicate within a team environment and interact across departments.
Preferred Qualifications, Capabilities, and Skills:
- 3+ years of relevant industry experience, preferably in reference data-related roles.
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About JPMorgan Chase

JPMorgan Chase
PublicJPMorgan Chase & Co. is an American multinational banking institution headquartered in New York City and incorporated in Delaware. It is the largest bank in the United States, and the world's largest bank by market capitalization as of 2025.
300,000+
Employees
New York City
Headquarters
$500B
Valuation
Reviews
10 reviews
3.8
10 reviews
Work-life balance
3.5
Compensation
4.0
Culture
3.8
Career
3.2
Management
2.8
68%
Recommend to a friend
Pros
Good benefits and compensation
Supportive colleagues and environment
Flexible work arrangements
Cons
Long hours and heavy workload
Management issues and lack of direction
High stress and expectations
Salary Ranges
44 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analytics Solutions Associate
1 reports
$139,000
total per year
Base
$107,000
Stock
-
Bonus
-
$139,000
$139,000
Interview experience
4 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer rate
50%
Experience
Positive 25%
Neutral 75%
Negative 0%
Interview process
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
In-person/Final Interview
5
Offer
Common questions
Behavioral/STAR
Past Experience
Culture Fit
Financial Knowledge
Case Study
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