At a Glance
- Tasks: Analyse complex data to support decision-making and improve performance in financial services.
- Company: Established financial services organisation with a focus on data-driven insights.
- Benefits: Competitive salary, hybrid working, and exposure to impactful projects.
- Other info: Great opportunity for career growth in a dynamic environment.
- Why this job: Make a real impact by influencing business decisions through your analytical skills.
- Qualifications: Strong SQL skills and experience with Power BI or Tableau required.
The predicted salary is between 55000 - 70000 £ per year.
Location: London (Hybrid - 2 days per week in the office)
Salary: 55,000 - 70,000 DOE
Industry: Financial Services
The Opportunity
I'm currently working with an established financial services organisation looking to hire a Data Analyst to join its growing team in London. The business uses complex financial and commercial data to support decision-making, improve performance and identify opportunities for greater efficiency. Data plays a key role in understanding trends, monitoring KPIs and delivering meaningful insights across the business.
You'll collaborate with stakeholders across different functions, helping them understand the data and make better commercial decisions. The ideal candidate will have strong SQL skills, experience with tools such as Power BI or Tableau, and the ability to communicate findings to technical and non-technical audiences. Financial services experience would be advantageous, particularly working with financial, operational or customer data.
If you're a Data Analyst looking to develop your career in financial services, take ownership of analytical projects and work closely with business stakeholders, this could be an excellent opportunity.
- Write and optimise SQL queries to extract and analyse data from multiple sources.
- Develop and maintain dashboards and reports using Power BI, Tableau or similar tools.
- Monitor KPIs, track performance and highlight areas requiring attention.
- Work with stakeholders across finance, operations, risk and other business functions.
- Investigate data discrepancies and help improve data accuracy and consistency.
- Deliver regular and ad hoc reporting to support business planning and decision-making.
- Automate manual reporting and improve analytical processes.
Essential Skills and Experience
- Proven experience as a Data Analyst or in a similar analytical role.
- Strong SQL skills, including extracting, joining and manipulating data.
- Experience with Power BI, Tableau or another data visualisation tool.
- Experience developing dashboards, reports and performance metrics.
- Strong attention to detail and commitment to data quality.
Skills and Experience
- Experience in financial services, banking, insurance, asset management or fintech.
- Experience analysing financial, transactional, customer, risk or operational data.
- Knowledge of financial products, business processes or regulatory reporting.
- Python experience for data analysis or automation.
- Advanced Excel skills, including formulas and pivot tables.
- Familiarity with cloud data platforms, data warehouses or modern analytics tools.
- Understanding of data governance and data quality.
Package and Benefits
- 55,000 - 70,000 salary, depending on experience.
- Hybrid working, with two days per week in the London office.
- Exposure to complex financial services data and commercially important projects.
- Opportunity to influence business decisions through data-driven insights.
Data Analyst - Work From Home employer: Oscar
Join a dynamic and innovative software and Business Intelligence organisation in Hertford, where you'll thrive in a hybrid work environment that promotes flexibility and collaboration. As a Data Consultant, you'll enjoy a varied role with opportunities for professional growth, including managing projects from inception to deployment and engaging with a European customer base. The company fosters a supportive culture that values continuous learning and offers exposure to exciting industry events, making it an excellent employer for those seeking meaningful and rewarding work.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst - Work From Home
✨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 Oscar!
✨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 Data Analyst - Work From Home at Oscar.
✨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 Oscar.
✨Apply Directly through Our Website
When you find a suitable opening like Data Analyst - Work From Home at Oscar, 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 Data Analyst - Work From Home
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 Oscar, 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 Oscar. 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 Oscar
✨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 Oscar!
✨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.
