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- Tasks: Troubleshoot data issues and support reference data for top finance professionals.
- Company: Join a passionate team at a leading data services firm.
- Benefits: Competitive salary, career growth, and a collaborative work environment.
- Why this job: Make an impact in finance by ensuring data accuracy and reliability.
- Qualifications: Bachelor’s degree and 3+ years in financial services with SQL and Python skills.
- Other info: Work with a global team and enhance your analytical skills.
The predicted salary is between 36000 - 60000 £ per year.
We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s data services group is looking for a Data Operations Analyst to join our dedicated team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world.
This exceptional individual will join a global team of analysts who monitor, validate, and support Security and Issuer reference data within the firm’s central reference data system.
RESPONSIBILITIES- Troubleshoot and resolve data discrepancies, monitor vendor SLAs, and communicate data issues to internal stakeholders.
- Implement proactive measures to identify and resolve data issues automatically.
- Handle internal client requests and inquiries, ensuring transparent support and leading communication on any SLA breaches.
- Assist in the onboarding of new datasets, validation rules, and user interface improvements, as well as participate in testing.
- Develop and document standardized processes for data support, monitoring, and quality assurance.
- Collaborate with global team members to ensure seamless transitions between support regions.
- Liaise with Business, Technology, and Operations leadership to ensure alignment on project objectives, deliverables, requirements, and status updates.
- Bachelor’s degree with a concentration in Computer Science or related discipline.
- 3+ years of experience in financial services, asset management, or hedge funds with a focus on data operation and reference data support.
- Expertise in reference data content from common financial service data providers such as Bloomberg, Refinitiv, Barra, FactSet, etc.
- Experience troubleshooting and resolving data issues, along with experience in engaging with data consumers.
- Programming skills in SQL and Python.
- Experience working with large data sets.
- Strong oral and written communication skills.
- Strong analytical and problem-solving skills, with a keen attention to detail.
- Commitment to the highest ethical standards.
Reference Data Analyst employer: Point72 Careers
Contact Detail:
Point72 Careers Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Reference Data Analyst
✨Tip Number 1
Network like a pro! Reach out to folks in the finance and data sectors on LinkedIn. Join relevant groups, attend webinars, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your SQL and Python projects. This is a great way to demonstrate your expertise in handling large datasets and troubleshooting data issues, which will definitely catch the eye of hiring managers.
✨Tip Number 3
Prepare for those interviews! Research common questions related to data operations and reference data support. Practice articulating your experience with financial services and how you’ve tackled data discrepancies in the past. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate individuals who align with our values. Tailor your application to highlight your analytical skills and commitment to quality assurance – it’ll make a difference!
We think you need these skills to ace Reference Data Analyst
Some tips for your application 🫡
Show Your Passion for Data: We want to see your enthusiasm for data in your application! Make sure to highlight any relevant experience or projects that showcase your love for data and how you've used it to solve problems.
Tailor Your CV and Cover Letter: Don’t just send the same old CV and cover letter. We’re looking for candidates who can connect their skills to our specific needs. Mention your experience with reference data and how it relates to the role of a Reference Data Analyst.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon and get straight to the point about your skills and experiences that make you a great fit for the team.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Point72 Careers
✨Know Your Data Inside Out
Make sure you brush up on your knowledge of reference data and the specific financial services mentioned in the job description. Familiarise yourself with data providers like Bloomberg and Refinitiv, as well as common issues that arise in data operations. This will show your passion for data and your readiness to tackle challenges.
✨Showcase Your Problem-Solving Skills
Prepare examples from your past experience where you've successfully resolved data discrepancies or improved processes. Be ready to discuss how you approached these problems, the tools you used (like SQL or Python), and the outcomes. This will demonstrate your analytical skills and attention to detail.
✨Communicate Clearly and Effectively
Since strong communication skills are crucial for this role, practice articulating your thoughts clearly. Think about how you would explain complex data issues to non-technical stakeholders. During the interview, be concise but thorough in your responses, ensuring you convey your ideas effectively.
✨Collaborate and Align
Highlight your experience working in teams and collaborating with different departments. Be prepared to discuss how you’ve liaised with business, technology, and operations teams in the past. This will show that you understand the importance of alignment on project objectives and can work seamlessly within a global team.