LRH16 Data Analyst
London
Cybernetic Controls Limited
We are a trusted UK recruitment services provider,offering expert staffing solutions across various sectors.Explore Cybernetic Controls todayDepartment: Data
Employment Type: Full Time
Location: London
Reporting To: Chief Technology Officer
Description
OverviewLRH is on a mission to create a truly data-driven repo market. Backed by the Kaizen RegTech Group, our startup works with the world’s leading banks, asset managers and hedge funds to develop a pioneering data solution designed to enhance trading activities in the €23 trillion UK and European repo markets. Our innovation provides these financial institutions with an unprecedented perspective on market dynamics.
https://www.londonreportinghouse.com
Job Summary:
We are seeking a motivated and detail-oriented Data Analyst to join our team starting immediately! This is an excellent opportunity for a recent graduate or someone early in their career to gain hands-on experience in data analysis and contribute to our data-driven decision-making processes. You will work closely with our data and engineering teams, and subject matter experts to analyse data, generate insights, and support various business functions. The role is on-site and you will be exposed to the business side of the organisation, as well as having an opportunity to get in front of clients and partners (quite a rare opportunity in the industry).
Key Responsibilities
- Collect, clean, and preprocess data from various sources.
- Perform exploratory analyses on financial data from real trades.
- Generate reports and visualisations to communicate findings to clients and stakeholders.
- Assist in the development and maintenance of dashboards and data tools.
- Cross-company collaboration to support data-driven projects and initiatives.
- Ensure data quality and integrity throughout.
Skills, Knowledge and Expertise
Experience and Qualifications:- Bachelor’s degree with a quantitative component (e.g. Data Science, Statistics, Computer Science, Mathematics, Economics, Physics etc.), or equivalent experience
- Proficiency in data analysis tools and languages (e.g. Python, R, SQL)
- Experience producing meaningful, informative data visualisations
- Strong analytical and problem-solving skills
- Excellent attention to detail and organisational skills
- Good communication and teamwork abilities
- Eagerness to learn and adapt in a fast-paced fintech startup environment
- Internship or project experience in data modelling and analysis
- Knowledge of statistical methods and techniques
- Familiarity with cloud platforms (e.g. AWS, Google Cloud, Azure)
- Familiarity with business intelligence tools (e.g. Quicksight, Tableau, Power BI)
- Understanding of machine learning concepts
- Interest in GenAI and its applications
- Experience with version control systems (e.g. Git)
- Knowledge of the financial markets would be an asset
Benefits
- A competitive salary package
- Office in the heart of The City: 5-minute walking distance from Bank, Cannon Street and St. Paul's station
- Access to additional office space in London’s iconic Gherkin 5 minutes from Liverpool Street Station
- 25 days’ holiday , as well as UK bank holidays
- Well-being allowance
- Build-your-skills allowance
- Private healthcare + dental
- Working within a fast-growing company that has a culture of empowerment, innovation and collaboration
- Awesome team of financial markets experts, data analysts and engineers
- Opportunity to play a key role in an exciting startup backed by the Kaizen RegTech Group
- Opportunities for continuous career growth and learning
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Azure Business Intelligence Computer Science Data analysis Data quality Economics Engineering FinTech GCP Generative AI Git Google Cloud Machine Learning Mathematics Physics Power BI Python QuickSight R SQL Statistics Tableau
Perks/benefits: Career development Competitive pay Startup environment
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.