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, flexible work options, 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 60000 - 80000 £ 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 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.
Senior Quantitative Data Operations Analyst employer: Dormont Manufacturing Co
Fidelity Asset Management is an exceptional employer, offering a dynamic work environment where data experts can thrive in the field of portfolio risk analytics. With a strong focus on employee growth and development, Fidelity provides access to cutting-edge technology and collaborative opportunities that empower team members to enhance their skills while contributing to impactful investment decisions. The company's commitment to quality and innovation, combined with its supportive culture, makes it an ideal place for professionals seeking meaningful and rewarding careers in finance.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Quantitative Data Operations Analyst
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working in risk analytics or data operations. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Prepare a portfolio or case studies that highlight your experience with data quality frameworks and market risk models. This will give you an edge during interviews and show that you mean business.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions related to data operations and risk management. Mock interviews with friends or mentors can help you nail your responses and boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Senior Quantitative Data Operations Analyst
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Senior Quantitative Data Operations Analyst. 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 expertise 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. Provide examples of how you've tackled data quality issues or improved reporting accuracy in previous roles. We love seeing how you’ve made an 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 Dormont Manufacturing Co
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of data you'll be working with, especially portfolio risk analytics. Brush up on your knowledge of security factor exposures, covariance matrices, and the specific vendors like Barra or Bloomberg that are mentioned in the job description.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, Python, and any other relevant tools. Bring examples of how you've used these skills to solve data quality issues or improve reporting accuracy in previous roles.
✨Demonstrate Problem-Solving Abilities
Think of specific instances where you identified and resolved data quality issues. Be ready to explain your thought process and the steps you took to root-cause problems, as this will show your analytical depth and proactive approach.
✨Communicate Clearly and Effectively
Since the role involves collaboration with various teams, practice articulating complex data concepts in a straightforward manner. Prepare to discuss how you’ve successfully communicated with both technical and investment teams in the past.
