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- Tasks: Join a dynamic team to optimise data operations and ensure smooth data transmission.
- Company: Be part of a leading hedge fund with billions in assets under management.
- Benefits: Enjoy a lucrative salary, bonuses, and flexible work-from-home options after settling in.
- Why this job: Work on impactful projects, collaborate with top teams, and enhance your technical skills.
- Qualifications: 2-7 years in data operations; strong coding skills in SQL, Python, or similar languages required.
- Other info: This is a newly created role with significant growth potential in a fast-paced environment.
The predicted salary is between 75000 - 125000 £ per year.
A high performing, multi-billion dollar AUM hedge fund is looking to make a newly created Data Analyst hire into their rapidly growing centralised Data Management team. Reporting into the Global Head of Data and taking on a highly visible role within the team, the hire will be working very closely with Operations, Product Control, Risk, Trading and Research teams to ensure the smooth transmission of data, in a role that has a highly technical/engineering angle.
You will optimize the operation and quality management of the internal data pipeline with oversight of raw data initially being onboarded through to the delivery of datapoints to front office/investment teams. You will use your technical knowledge of languages such as SQL, Python, VBA, and Matlab to conduct quality checks and anomaly identification, by interrogating complex dataset analysis.
The hire will act as the main interface between data sourcing and data engineering and be the point of contact for Traders. The hire will also take on ad hoc projects working with front office and technology teams to assist with testing new dataset onboarding platforms, setting data governance metrics, and assisting with developing a centralized data management platform.
Candidates should have 2 – 7 years of experience as a Data Operations Specialist, Data Solutions Analyst, or Data Governance Analyst at a hedge fund, asset manager, or a major data vendor. Candidates must have a strong academic profile with experience using advanced coding/programming languages to analyse large datasets ideally as part of an existing Data team within the financial services sector.
The role is offering a base salary of up to £125K plus a bonus that can be a large percentage of base for a top performer. Whilst the hire should expect to work a 5-day office week initially, it will be possible to work from home 1-2 days per week once established in the role.
Contact Detail:
Mondrian Alpha Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Operations & Governance Analyst/Engineer - Major Hedge Fund – Lucrative Total Comp Package
✨Tip Number 1
Familiarise yourself with the specific data management tools and technologies mentioned in the job description, such as SQL, Python, VBA, and Matlab. Having hands-on experience or projects that showcase your proficiency in these languages will set you apart from other candidates.
✨Tip Number 2
Network with professionals already working in hedge funds or similar financial institutions. Attend industry events or join relevant online forums to connect with individuals who can provide insights into the company culture and expectations for the role.
✨Tip Number 3
Prepare to discuss your previous experiences in data operations and governance during interviews. Be ready to share specific examples of how you've optimised data pipelines or improved data quality in past roles, as this will demonstrate your capability to handle the responsibilities outlined in the job description.
✨Tip Number 4
Research the hedge fund's recent projects or initiatives related to data management. Being knowledgeable about their current challenges and how you can contribute to solving them will show your genuine interest in the role and the company.
We think you need these skills to ace Data Operations & Governance Analyst/Engineer - Major Hedge Fund – Lucrative Total Comp Package
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data operations, governance, and analysis. Emphasise your technical skills in SQL, Python, VBA, or Matlab, and any previous roles in hedge funds or asset management.
Craft a Compelling Cover Letter: Write a cover letter that showcases your understanding of the role and the importance of data management in a hedge fund environment. Mention specific projects or experiences that demonstrate your ability to optimise data pipelines and conduct quality checks.
Highlight Technical Proficiency: In your application, clearly outline your technical skills and experience with complex datasets. Provide examples of how you've used programming languages to solve problems or improve processes in previous roles.
Showcase Collaboration Skills: Since the role involves working closely with various teams, highlight your experience in cross-functional collaboration. Mention any instances where you successfully liaised between data sourcing and engineering teams or worked on ad hoc projects with front office staff.
How to prepare for a job interview at Mondrian Alpha
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in SQL, Python, VBA, and Matlab during the interview. Prepare examples of how you've used these languages to analyse large datasets or solve complex problems in previous roles.
✨Understand Data Governance
Familiarise yourself with data governance principles and metrics. Be ready to discuss how you would implement these in the context of a hedge fund, as this role involves setting data governance standards.
✨Demonstrate Collaboration Experience
Since this position requires working closely with various teams like Operations, Trading, and Research, prepare to share examples of successful collaborations from your past experiences. Highlight your ability to communicate effectively across different departments.
✨Prepare for Technical Questions
Expect technical questions related to data management and analysis. Brush up on your knowledge of data pipelines and quality checks, and be prepared to discuss how you would approach anomaly identification in datasets.
