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- Tasks: Tackle complex data modeling challenges in financial markets daily.
- Company: Join a forward-thinking company focused on strategic data standardization initiatives.
- Benefits: Enjoy opportunities for professional growth and collaboration on diverse client projects.
- Why this job: Shape the future of financial data reporting while working with cutting-edge technology.
- Qualifications: Bring extensive experience in data modeling and a strong understanding of financial products.
- Other info: Ideal for proactive individuals eager to take ownership and drive impactful solutions.
The predicted salary is between 36000 - 60000 £ per year.
About the Company I am currently recruiting for an experienced Data Modeller/ Business Analyst with solid knowledge of the financial products’ lifecycle to deliver our clients’ strategic data standardisation initiatives. You will be building the future of data and reporting for financial markets! What you’ll do day to day working on complex data modelling challenges for financial products, financial transactions, and associated regulatory reporting obligations Build and enhance industry data and functional models for Securities, Securities Finance, Derivatives, Commodities, Equities and FX Deliver core model design improvements by identifying common data patterns across asset classes and product types Analyse our clients’ existing data estate to assist them integrating with our technology platform Translate applicable rules and regulations into functional logic to support our clients’ data reporting obligations Be responsible for taking requirements through to delivery, working to implementation deadlines and presenting to industry working groups Manage multiple client projects with overlapping scope and release schedule, ensuring continuous delivery across our company’s portfolio What they’re looking for Extensive experience in a data modelling, data engineering, quant or business analysis role (with a strong data focus in each case) in the financial markets domain Solid knowledge of financial products and their transaction lifecycle in at least one of the areas: Securities, Equities, Derivatives, Commodities, FX Experience of agile techniques, product lifecycle and project management An analytical mind with strong problem-solving and design-thinking capabilities Strong communication and presentation skills Proactivity and a genuine desire for taking ownership. Non essential but highly desirable Experience with regulatory reporting or other large-scale data collection implementations in a financial services firm Experience working with different post trade messaging protocols (e.g. FpML, FIX, ISO 20022) Experience coding with modern programming languages Prior client service or consulting experience
Financial Data Analyst employer: SearchWorks
Contact Detail:
SearchWorks Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Financial Data Analyst
✨Tip Number 1
Familiarize yourself with the specific financial products mentioned in the job description, such as Securities, Derivatives, and FX. Understanding their transaction lifecycles will give you a significant edge during interviews.
✨Tip Number 2
Highlight any experience you have with data modelling and analysis in your previous roles. Be prepared to discuss specific projects where you successfully managed complex data challenges, as this will demonstrate your capability to handle the responsibilities of the role.
✨Tip Number 3
Showcase your knowledge of regulatory reporting and compliance, especially if you have experience with large-scale data collection implementations. This is a highly desirable skill that can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your experience with agile methodologies and project management. Being able to articulate how you've successfully delivered projects on time while managing multiple client needs will be crucial in demonstrating your fit for the role.
We think you need these skills to ace Financial Data Analyst
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Financial Data Analyst position. Understand the key responsibilities and required skills, especially focusing on data modelling and financial products.
Highlight Relevant Experience: In your CV and cover letter, emphasize your extensive experience in data modelling, data engineering, or business analysis within the financial markets. Provide specific examples of projects you've worked on that align with the job requirements.
Showcase Analytical Skills: Demonstrate your analytical mindset and problem-solving abilities in your application. Mention any relevant tools or methodologies you have used, particularly in relation to financial transactions and regulatory reporting.
Tailor Your Application: Customize your application materials to reflect the language and terminology used in the job description. This shows that you understand the industry and are genuinely interested in the role.
How to prepare for a job interview at SearchWorks
✨Showcase Your Data Modelling Experience
Be prepared to discuss your previous experience in data modelling and how it relates to financial products. Highlight specific projects where you tackled complex data challenges, as this will demonstrate your expertise and problem-solving skills.
✨Understand Financial Products Thoroughly
Make sure you have a solid understanding of the financial products mentioned in the job description, such as Securities, Derivatives, and FX. Being able to speak knowledgeably about their lifecycle will impress the interviewers and show that you're a good fit for the role.
✨Demonstrate Agile Methodology Knowledge
Since the company values experience with agile techniques, be ready to discuss how you've applied agile methodologies in past projects. Share examples of how you managed project timelines and collaborated with teams to deliver results.
✨Prepare for Technical Questions
Expect technical questions related to data engineering and programming languages. Brush up on relevant coding concepts and be ready to explain how you've used them in your work, especially in relation to regulatory reporting or data collection implementations.
