At a Glance
- Tasks: Own data, reporting, and automation initiatives in a dynamic investment management environment.
- Company: Join a specialist investment management firm with a focus on technology and data.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Be part of a small, experienced team in a fast-paced, innovative setting.
- Why this job: Make a real impact by designing scalable data solutions in finance.
- Qualifications: 3-5+ years in data roles with strong SQL, Power BI, and Python skills.
The predicted salary is between 59400 - 72600 £ per year.
Referment is working with a specialist investment management and advisory firm to hire an Investment BI & Data Analyst into its London team. This is a particularly interesting opportunity for someone who sits at the intersection of investment data, technology and financial markets and wants considerably more ownership than a traditional BI or reporting role. The firm operates across London and Dubai, with a small, experienced team where technology, data and automation are central to the way the business operates.
The role involves taking ownership of data, reporting and automation initiatives across the business, helping to design the data architecture underpinning investment, client, risk, treasury, P&L, exposure and management reporting. Importantly, this is not simply a Power BI/report-building position. You’ll be expected to understand how data moves through an investment business, determine how it should be structured and controlled, and build reliable, scalable solutions around it. You’ll work with data covering trades, positions, cash, securities, portfolios, market data and accounting, integrating information from systems and counterparties including private banks, custodians, fund administrators, brokers and market-data providers.
The remit will include:
- Designing and maintaining data models and architecture
- Building automated data pipelines and integrations
- Working with APIs, structured files and external data feeds
- Developing automated reporting and analytics
- Data validation, reconciliation and transformation
- Building interfaces into Power BI and other internal tools
- Reducing reliance on spreadsheets and manual processes
- Creating monitoring and exception processes around critical data flows
What we’re looking for:
We’re particularly interested in candidates with strong practical experience across SQL, Power BI/DAX, Python, APIs/JSON, ETL/ELT, data modelling and automated data pipelines. Crucially, you’ll need 3–5+ years' experience within a hedge fund, asset manager, family office, investment bank, financial technology business or similarly data-intensive financial environment. Given the size of the team, this will suit someone who is hands-on, curious and highly autonomous. You should be comfortable taking a loosely defined problem, getting into the underlying data and owning the solution through design, build, testing, documentation and ongoing support. If you’ve built investment data solutions rather than simply consumed them, we’d be particularly interested in speaking with you.
Investment BI and Data Analyst - Investment Management (B5EC280) employer: Referment
Referment is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation. As a Finance Director, you will not only lead the finance function but also play a pivotal role in shaping the company's growth trajectory, with ample opportunities for professional development and advancement. Located in a vibrant B2B technology hub, the company provides a supportive environment where your contributions are valued and rewarded.
StudySmarter Expert Advice🤫
We think this is how you could land Investment BI and Data Analyst - Investment Management (B5EC280)
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We think you need these skills to ace Investment BI and Data Analyst - Investment Management (B5EC280)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Referment, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Referment. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Referment
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Referment!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
