At a Glance
- Tasks: Analyse data and deliver insights to enhance client experiences.
- Company: Join a leading global fund manager with a high-performing team.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Dynamic work environment with potential for career advancement.
- Why this job: Be at the forefront of investment and data infrastructure while making a real impact.
- Qualifications: 1-2 years experience in data analysis, strong skills in SQL and Python.
The predicted salary is between 30000 - 40000 £ per year.
We’re partnering with a leading globally operating fund manager to hire a Data Analyst into their high-performing Global Client team on an initial 12 month fixed term contract. The role requires strong technical skills in SQL & Python as well as experience with data warehousing tools (ideally Snowflake). This is a great opportunity for a data-driven professional looking to work at the intersection of investment, data infrastructure, and client delivery.
- 1–2 years + experience in a Data Analyst or similar role
- Strong technical skills in Python & SQL
- Experience with data warehousing tools (ideally Snowflake)
- Some exposure to data visualisation tools (e.g. Tableau) - preferred not essential
- Solid understanding of data governance, quality, and classification
- Master’s degree in Data Science, Analytics, Computer Science or similar - preferred not essential
Reporting Data Analyst with SQL and Python in London employer: Ramsey Portia
Join a dynamic and innovative team at a leading global fund manager, where your skills as a Reporting Data Analyst will be valued and nurtured. With a strong emphasis on professional development, you will have access to cutting-edge tools and technologies, fostering a collaborative work culture that prioritises employee growth and engagement. Located in a vibrant city, this role offers the unique advantage of working at the forefront of investment and data infrastructure, making a meaningful impact on client delivery.
StudySmarter Expert Advice🤫
We think this is how you could land Reporting Data Analyst with SQL and Python in London
✨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 Ramsey Portia!
✨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 Reporting Data Analyst with SQL and Python at Ramsey Portia.
✨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 Ramsey Portia.
✨Apply Directly through Our Website
When you find a suitable opening like Reporting Data Analyst with SQL and Python at Ramsey Portia, 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 Reporting Data Analyst with SQL and Python in London
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 Ramsey Portia, 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 Ramsey Portia. 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 Ramsey Portia
✨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 Ramsey Portia!
✨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.
