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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: Competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Make a real impact on investment strategies with cutting-edge data analytics.
- 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 ÂŁ 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: Fidelity Investments
Contact Detail:
Fidelity Investments 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 already working at Fidelity. A friendly chat can open doors and give you insider info on what they're really looking for.
✨Tip Number 2
Prepare for interviews by diving deep into portfolio risk analytics. Brush up on your SQL and Python skills, and be ready to discuss how you've tackled data quality issues in the past. Show us your analytical prowess!
✨Tip Number 3
Don’t just wait for job openings; create your own opportunities! Apply through our website and express your passion for data operations. We love seeing candidates who take the initiative.
✨Tip Number 4
Follow up after interviews with a thank-you note. It’s a simple gesture that shows your enthusiasm for the role and keeps you fresh in their minds. Plus, it’s a great way to reiterate your fit for the team!
We think you need these skills to ace Associate, Quantitative Data Operations
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Associate in Quantitative Data Operations. 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 and data management.
Showcase Your Analytical Skills: In your application, don’t shy away from showcasing your analytical prowess. Mention any projects where you’ve tackled data quality issues or improved reporting accuracy. We love seeing how you’ve used your skills to make a real impact!
Apply Through Our Website: We encourage you to apply through our website for a smoother 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 Fidelity Investments
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of data relevant to portfolio risk analytics. Brush up on your knowledge of security factor exposures, covariance matrices, and the tools like Bloomberg PORT or BarraOne. Being able to discuss these confidently will show that you’re not just familiar with the concepts but can also apply them.
✨Demonstrate Problem-Solving Skills
Prepare to share examples of how you've tackled data quality issues in the past. Think about specific instances where you identified root causes and collaborated with teams to resolve them. This will highlight your analytical depth and proactive approach, which are crucial for this role.
✨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 few technical questions or scenarios to demonstrate your problem-solving skills. This will help you stand out as someone who can navigate complex data environments effectively.
✨Communicate Clearly and Effectively
Since this role involves collaboration across technical and investment teams, practice articulating your thoughts clearly. Prepare to explain complex data concepts in simple terms, as this will showcase your ability to bridge the gap between technical and non-technical stakeholders.
