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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 group in finance.
- Benefits: Competitive salary, professional development, 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: Dynamic global team with opportunities for growth and innovation.
The predicted salary is between 36000 - 60000 £ per year.
ABOUT: 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.
REQUIREMENTS:
- 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 in London employer: Point72 Asset Management, L.P
Contact Detail:
Point72 Asset Management, L.P Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Reference Data Analyst in London
✨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
Prepare for those interviews by brushing up on your SQL and Python skills. We all know that technical questions can pop up, so practice coding challenges and be ready to discuss your past experiences with data discrepancies and solutions.
✨Tip Number 3
Showcase your problem-solving skills! When you get the chance to chat with potential employers, share specific examples of how you've tackled data issues in the past. This will demonstrate your analytical prowess and attention to detail.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Reference Data Analyst in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Reference Data Analyst role. Highlight your experience in financial services and any relevant programming skills, like SQL and Python. We want to see how your background aligns with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data and how you can contribute to our team. Be sure to mention your experience with data operations and any specific tools you've used.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled data discrepancies or resolved issues in the past. We love candidates who can demonstrate strong analytical skills and attention to detail, so don't hold back!
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’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Point72 Asset Management, L.P
✨Know Your Data Inside Out
Make sure you brush up on your knowledge of reference data and the specific financial services data providers mentioned in the job description. Being able to discuss how you've worked with data from sources like Bloomberg or Refinitiv will show that you're not just familiar with the concepts, but that you can apply them practically.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've successfully troubleshot data discrepancies in the past. Use the STAR method (Situation, Task, Action, Result) to structure your answers, highlighting your analytical skills and attention to detail. This will demonstrate your ability to handle the responsibilities outlined in the role.
✨Communicate Clearly and Confidently
Since strong communication skills are a must for this role, practice articulating your thoughts clearly. Be ready to explain complex data issues in simple terms, as you'll need to liaise with various stakeholders. Consider doing mock interviews with friends or using online platforms to refine your delivery.
✨Familiarise Yourself with SQL and Python
Brush up on your programming skills, especially in SQL and Python, as these are crucial for the role. Be prepared to discuss any relevant projects or experiences where you've used these languages to manipulate large datasets. If possible, try to solve a few coding challenges beforehand to get into the right mindset.