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- Tasks: Join a dynamic team ensuring accurate portfolio risk analytics for investment decisions.
- Company: Fidelity Asset Management, a leader in innovative financial solutions.
- Benefits: Full-time role with competitive salary and opportunities for professional growth.
- Other info: Collaborative environment with a focus on quality and efficiency.
- Why this job: Make a real impact on investment strategies using your data expertise.
- Qualifications: Bachelor's degree in a quantitative field and 3+ years in data operations.
The predicted salary is between 36000 - 60000 £ per year.
Quantitative Research and Investments (QRI) is seeking a highly motivated data expert in the domain of portfolio risk analytics to join a risk platform operations team responsible for ensuring that all vendor and internal portfolio risk analytics used for risk management and portfolio construction across Fidelity are delivered consistently, accurately and on a timely basis.
The Risk Platform Operations team are the stewards of risk analytics data for Fidelity Asset Management. They focus on quality control of all data that feeds into portfolio risk analytics, including security factor exposures and proxies, factor returns and covariance matrices, fundamentals data, security T&Cs, and portfolio holdings.
In this role, you will utilize domain expertise necessary to root-cause daily issues effectively, work with internal and external data providers to resolve issues at source, answer portfolio and risk manager questions, and develop automated systems for identifying data quality issues.
The Skills and Expertise You Bring:
- You bring a unique blend of technical acumen, analytical depth, and domain expertise that enables Fidelity Asset Management to make informed, data-driven investment decisions.
- Your work ensures the integrity, accuracy, and timeliness of risk analytics and data operations, directly supporting portfolio construction and risk management.
- Act as a steward of data assets critical to risk management and portfolio construction.
- Lead quality service efforts to address overnight data feed issues, enabling fast, seamless responses to upstream problems and insulating production and research teams.
- Update and verify multi-factor risk model inputs and outputs prior to client delivery.
- Ensure access to accurate, timely, and relevant portfolio risk analytics by collaborating with technology and business partners to resolve data quality issues at the source.
- Analyze systems and processes to identify efficiencies and improve reporting accuracy and timeliness.
- Apply experience with market risk models from vendors such as Barra, Axioma, Northfield, or Bloomberg.
- Leverage strong analytical skills to comprehend large datasets and implement effective quality controls.
- Operate with a proactive, self-motivated approach, meeting objectives with minimal direction.
- Utilize vendor-provided risk data and tools including Bloomberg PORT, BarraOne, RiskManager, and/or Axioma.
- Demonstrate deep knowledge of financial data across security, company, portfolio, and index levels, including pricing for equities, bonds, and derivatives.
- Employ technical proficiency in SQL, Python, Snowflake, and/or Oracle, along with data quality frameworks.
- Hold a Bachelor's degree (or higher) in mathematics, statistics, engineering, computer science, finance, or a related quantitative field.
- Bring 3+ years of experience in global data operations or support teams within peer firms, with a proven track record of delivering value.
- Apply expertise in anomaly detection methods, data quality workflows, and statistical best practices.
- Communicate effectively across technical and investment teams.
- Navigate complex data environments and support the necessary technology and analytics infrastructure.
- Identify root causes of data quality issues and collaborate with teams and providers to resolve them.
- Create automated processes to detect errors and ensure high-quality data for investment decision-making.
- Document procedures and validate data to maintain transparency and reliability.
- Possess domain expertise in investment management across risk management, portfolio management, trading, and investment operations.
The Team:
The Risk Platform Operations team is an integral part of the Quantitative Research and Investing (QRI) division in Asset Management. QRI is responsible for the management and development of quantitative investment strategies and solutions while providing high quality quantitative, data-driven support to Fidelity's fundamental investment professionals, ensuring they have access to the most relevant data and advanced quantitative analysis.
Associate, Quantitative Data Operations in London employer: Soteria Reinsurance Ltd.
Contact Detail:
Soteria Reinsurance Ltd. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Associate, Quantitative Data Operations in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your analytical skills. Use real-life examples from your experience to demonstrate how you've tackled data quality issues or improved processes.
✨Tip Number 3
Don’t just apply anywhere; focus on companies that align with your values and expertise. Check out our website for roles that match your skills in quantitative data operations and portfolio risk analytics.
✨Tip Number 4
Follow up after interviews! A quick thank-you email can go a long way in keeping you top of mind. Mention something specific from your conversation to show your genuine interest in the role.
We think you need these skills to ace Associate, Quantitative Data Operations in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the skills and expertise mentioned in the job description. Highlight your experience with data operations, risk analytics, and any relevant technical skills like SQL or Python. We want to see how you fit into our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about quantitative data operations and how your background aligns with our needs. Be sure to mention specific experiences that demonstrate your analytical depth and problem-solving skills.
Showcase Your Technical Skills: Since this role requires a strong technical acumen, don’t shy away from detailing your proficiency in tools like Bloomberg PORT or Axioma. We love seeing candidates who can navigate complex data environments and have hands-on experience with data quality frameworks.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Soteria Reinsurance Ltd.
✨Know Your Data Inside Out
Make sure you brush up on your knowledge of portfolio risk analytics and the specific data tools mentioned in the job description, like Bloomberg PORT and Axioma. Being able to discuss how you've used these tools in past roles will show that you're not just familiar with them, but that you can leverage them effectively.
✨Demonstrate Problem-Solving Skills
Prepare examples of how you've identified and resolved data quality issues in previous positions. The interviewers will want to see your analytical depth and technical acumen, so be ready to walk them through your thought process and the steps you took to root-cause problems.
✨Showcase Your Collaboration Skills
Since this role involves working closely with both technical and investment teams, think of instances where you've successfully collaborated across departments. Highlight your communication skills and how you’ve ensured that everyone is on the same page when tackling data challenges.
✨Be Proactive and Self-Motivated
The job calls for a proactive approach, so come prepared to discuss how you've taken initiative in past roles. Share examples of how you've improved processes or implemented automated systems to enhance data quality, demonstrating that you can meet objectives with minimal direction.