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- Tasks: Analyze data, create reports, and support business functions in a dynamic start-up.
- Company: Join an ambitious start-up revolutionizing the repo market with innovative data solutions.
- Benefits: Enjoy 25 days holiday, private healthcare, and a learning & development budget.
- Why this job: Gain hands-on experience in data analysis while collaborating with top financial institutions.
- Qualifications: Bachelor’s degree in a quantitative field and proficiency in Python, R, and SQL required.
- Other info: This role offers direct client interaction and exposure to business operations.
The predicted salary is between 28000 - 42000 £ per year.
Data Analyst – Python
London
£35,000 – £40,000 + 25 Days Holiday + Private Healthcare + L&D Budget
My client is an ambitious start-up dedicated to revolutionising the repo market through data-driven strategies.
With major financial backing this start-up collaborates with top-tier banks, asset managers, and hedge funds to develop groundbreaking data solutions aimed at optimising trading operations in the €23 trillion UK and European repo markets.
Their innovative approaches offer these financial institutions a unique insight into market dynamics.
They are looking for an enthusiastic and meticulous Data Analyst to join their team immediately.
This role is perfect for recent graduates or early-career professionals seeking hands-on experience in data analysis while contributing to data-driven decision-making.
Apply Now – if you want to join this exciting start-up and grow your data analysis skills!
Key Activities and Responsibilities:
- You will work closely with our data and engineering teams, along with subject matter experts, to analyse data, glean insights, and support various business functions.
- This role is on-site and offers exposure to the business aspects of the organisation, along with the rare opportunity to interact directly with clients and partners.
- Collect, clean, and preprocess data from multiple sources.
- Conduct exploratory analyses on financial data derived from actual trades.
- Create reports and visualisations to convey findings to clients and stakeholders.
- Assist in the creation and upkeep of dashboards and data tools.
- Collaborate across the company to support data-driven projects and initiatives.
- Ensure data quality and integrity are upheld throughout.
Experience and Qualifications:
- Bachelor’s degree in a quantitative field (e.g., Data Science, Statistics, Computer Science, Mathematics, Economics, Physics), or equivalent experience.
- Proficiency with data analysis tools and languages such as Python, R, and SQL.
- Experience in generating meaningful and informative data visualisations.
- Strong analytical and problem-solving capabilities.
- Exceptional attention to detail and organisational skills.
- Effective communication and teamwork skills.
- A keen willingness to learn and adapt in a fast-paced fintech start-up environment.
Data Analyst – Python
London
£35,000 – £40,000 + 25 Days Holiday + Private Healthcare + L&D Budget
Data Analyst employer: Opus Recruitment Solutions
Contact Detail:
Opus Recruitment Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Familiarize yourself with the specific data analysis tools mentioned in the job description, especially Python, R, and SQL. Consider working on personal projects or contributing to open-source projects that showcase your skills in these areas.
✨Tip Number 2
Since this role involves collaboration with various teams, practice your communication skills. Engage in discussions about data analysis in online forums or local meetups to build confidence in conveying complex ideas clearly.
✨Tip Number 3
Research the repo market and understand its dynamics. Being knowledgeable about the industry will not only help you during interviews but also demonstrate your genuine interest in the company's mission.
✨Tip Number 4
Prepare to discuss your analytical process and how you approach problem-solving. Think of examples from your academic or project work where you successfully analyzed data and derived insights, as this will be crucial in showcasing your fit for the role.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant skills and experiences that align with the job description. Emphasize your proficiency in Python, R, and SQL, as well as any projects or coursework related to data analysis.
Craft a Compelling Cover Letter: Write a cover letter that showcases your enthusiasm for the role and the company. Mention specific reasons why you want to work for this start-up and how your background makes you a great fit for their team.
Showcase Your Analytical Skills: In your application, provide examples of past experiences where you successfully analyzed data or created visualizations. This could be from academic projects, internships, or personal projects that demonstrate your analytical capabilities.
Highlight Teamwork and Communication: Since the role involves collaboration across teams, emphasize your teamwork and communication skills. Share instances where you worked effectively in a group setting or communicated complex data insights to non-technical stakeholders.
How to prepare for a job interview at Opus Recruitment Solutions
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python, R, and SQL. Bring examples of past projects where you utilized these tools for data analysis and visualization. This will demonstrate your hands-on experience and technical capabilities.
✨Demonstrate Analytical Thinking
During the interview, be ready to solve a case study or a problem related to data analysis. This will allow you to showcase your analytical and problem-solving skills, which are crucial for the role.
✨Highlight Attention to Detail
Since the role requires meticulous data handling, share specific instances where your attention to detail made a significant impact on a project. This could involve cleaning data or ensuring data integrity.
✨Express Your Willingness to Learn
As a start-up, they value adaptability and a growth mindset. Share your enthusiasm for learning new tools and techniques in data analysis, and how you plan to contribute to their innovative environment.
