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For Companies At a Glance
- Tasks: Analyse data, build models, and create visualisations to support investment decisions.
- Company: Fast-growing FinTech company revolutionising data insights for investors.
- Benefits: Competitive salary, training, and a chance to work with cutting-edge technologies.
- Why this job: Join a dynamic team and make a real impact in the finance sector.
- Qualifications: Proficiency in Python, strong statistical knowledge, and a passion for finance.
- Other info: Great opportunities for growth and learning in a supportive environment.
The predicted salary is between 50000 - 70000 £ per year.
Oxford Data Plan is a fast-growing FinTech company providing alternative data and KPI tracking for 200+ listed companies worldwide. We help fundamental investors make better decisions with proprietary data insights. Founded in 2022, we've grown to over 70 people and are backed by leading investors. You will report to one of our Data Science Managers.
Responsibilities
- Analyse data, build, validate, and test prototype models in Jupyter.
- Produce data visualisations in Python to inspect correlations and create dashboards with PowerBI.
- Deploy new jobs to production using Docker and AWS technologies.
- Monitor, debug and maintain production code.
- Conduct equity research on companies, and apply domain knowledge to improve models.
- Support the Evaluation team by exploring new potential data sources, or building new web scrapers.
Essential skills
- Proficiency in Python: Ability to write functional, reproducible, and well documented code.
- Proficient with typical data scientist modules (pandas, numpy, matplotlib, scikit-learn).
- Strong Statistical knowledge: Good understanding of fundamental statistical concepts (e.g. bias, variance, R-squared).
- Good understanding of the theory and practice of linear regression.
- Self-motivated and autonomous individual.
- Significant training and support will be provided; however, we expect a successful candidate to quickly take full ownership of their work and proactively make an impact in ODP.
- Strong interest in a career in finance or business.
- Excellent problem-solving ability and judgment.
- Experience with Git.
- Experience working with databases and using SQL.
- Good experience/knowledge of the finance sector.
- Proficient in web-scraping – at least with requests, ideally with selenium or other web-scraping packages.
- Advanced knowledge of time-series modelling or Bayesian statistics.
- Experience working with AWS.
- Experience creating visualisations with Power BI.
Data Scientist in England employer: Oxford Data Plan
Contact Detail:
Oxford Data Plan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in England
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data visualisations and models. Use platforms like GitHub to share your projects and demonstrate your proficiency in Python and other tools mentioned in the job description.
✨Tip Number 3
Prepare for interviews by brushing up on your statistical knowledge and problem-solving skills. Be ready to discuss your experience with AWS, Docker, and SQL, as well as how you've applied these in real-world scenarios.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Scientist in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with Python, data visualisation, and any relevant projects you've worked on. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include links to your GitHub or any portfolio showcasing your data science projects. This gives us a chance to see your coding style and problem-solving skills in action. Don't be shy, show us what you've got!
Craft a Compelling Cover Letter: Your cover letter should reflect your passion for finance and data science. Tell us why you're excited about this role at Oxford Data Plan and how you can contribute to our team. Make it personal and engaging!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Oxford Data Plan
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially with libraries like pandas, numpy, and scikit-learn. Be ready to discuss how you've used these tools in past projects, as well as demonstrate your ability to write clean, reproducible code.
✨Show Off Your Statistical Knowledge
Prepare to talk about fundamental statistical concepts and how they apply to data science. Brush up on linear regression theory and practice, and be ready to explain how you’ve used these concepts in real-world scenarios.
✨Get Familiar with Data Visualisation Tools
Since you'll be creating dashboards with Power BI, it’s a good idea to have some examples of your work ready to share. Practice explaining your visualisations and the insights they provide, as this will showcase your ability to communicate complex data effectively.
✨Demonstrate Your Problem-Solving Skills
Be prepared to tackle some problem-solving questions during the interview. Think of examples from your experience where you faced challenges and how you approached them. This will highlight your analytical thinking and judgement, which are crucial for a role in data science.