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For Companies At a Glance
- Tasks: Join a team ensuring accurate and timely 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.
- 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.
- Other info: Dynamic team environment with a focus on quality and efficiency.
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 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
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working at Fidelity or similar firms. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills. Make sure you're comfortable discussing SQL, Python, and data quality frameworks. We want you to shine when it comes to showcasing your analytical prowess!
✨Tip Number 3
Showcase your problem-solving skills! Be ready to discuss how you've tackled data quality issues in the past. Real-life examples will help us see how you think and operate under pressure.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Associate, Quantitative Data Operations
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Associate, Quantitative Data Operations role. Highlight your experience with data quality, risk analytics, and any relevant technical skills like SQL or Python. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data operations and how your skills can contribute to our team. Be sure to mention specific experiences that relate to portfolio risk analytics.
Showcase Your Analytical Skills: In your application, don’t forget to showcase your analytical skills. Mention any projects where you’ve dealt with large datasets or resolved data quality issues. We love seeing how you’ve applied your expertise in real-world scenarios!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative to connect with us directly!
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. Think about specific instances where you had to root-cause a problem and how you collaborated with teams to fix it. This will highlight your analytical depth and proactive approach.
✨Showcase Your Technical Proficiency
Be ready to discuss your experience with SQL, Python, and any other relevant technologies. You might even want to prepare a small project or example that demonstrates your technical skills and how they relate to data operations. This will help you stand out as a candidate who can hit the ground running.
✨Communicate Clearly and Confidently
Since the role involves working with both technical and investment teams, practice explaining complex concepts in simple terms. During the interview, focus on clear communication to demonstrate that you can bridge the gap between data operations and investment management effectively.
