At a Glance
- Tasks: Analyse financial data and support insights using cutting-edge AI technologies.
- Company: Dynamic financial services firm with a focus on innovation.
- Benefits: Hands-on experience, mentorship from experts, and opportunities for growth.
- Other info: Collaborative team environment with a focus on learning and development.
- Why this job: Kickstart your career in finance while working with real-world data and advanced tools.
- Qualifications: Degree in Finance or related field; some data analysis experience preferred.
The predicted salary is between 31500 - 38500 £ per year.
We are looking for an enthusiastic and detail-oriented Market Data Analyst to join our growing team. This is a fantastic opportunity for a graduate, or someone early in their career, to develop hands‑on experience working with real-world financial data across a diverse range of financial institutions, including banks, asset managers, hedge funds, insurance firms, and pension funds. You will be supported by experienced colleagues while working with industry-leading proprietary software and exciting AI technologies to help deliver meaningful market insights.
Responsibilities
- Assist in gathering, cleaning, and maintaining market datasets from internal and external sources
- Support the analysis of client data under the guidance of senior analysts
- Learn and utilise industry-leading proprietary software platforms to process and visualise market data
- Assist in leveraging AI and machine learning tools to help automate data processing and surface actionable insights
- Help build and maintain dashboards and reports using tools like Tableau, Power BI, or similar
- Support senior team members in preparing materials for financial institution clients, ensuring data is accurate and delivered on time
- Monitor data quality and flag discrepancies across various datasets
- Present findings clearly to team members and contribute to broader stakeholder reporting
- Collaborate with colleagues across various functional teams to support data projects
Skills and Qualifications
- Bachelor's degree in Finance, Economics, Statistics, Mathematics, or a related field
- Some exposure to data analysis, whether through internships, placements, or academic projects
- Basic proficiency in Excel and an eagerness to develop skills in SQL and Python
- A genuine interest in financial markets and how data drives decision-making
- Curiosity about AI and its applications in financial services
- Strong attention to detail and willingness to learn
- Good communication skills and a collaborative attitude
Graduate Market Data Analyst employer: Doist
Brink's is an exceptional employer that fosters a collaborative and innovative work culture, empowering employees to drive global commercial strategies in the ATM lifecycle solutions sector. With a strong focus on professional development and growth opportunities, employees are encouraged to expand their skills while contributing to sustainable growth and operational excellence. Located in a dynamic environment, Brink's offers unique advantages such as a diverse team and the chance to build long-term partnerships with global customers, making it a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Graduate Market Data Analyst
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Doist!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Graduate Market Data Analyst at Doist.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Doist.
✨Apply Directly through Our Website
When you find a suitable opening like Graduate Market Data Analyst at Doist, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Graduate Market Data Analyst
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 Doist, 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 Doist. 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 Doist
✨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 Doist!
✨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.
