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For Companies At a Glance
- Tasks: Analyse data, build models, and create dashboards to drive financial insights.
- Company: Fast-growing FinTech company revolutionising data for investors.
- Benefits: Competitive salary, training, and a vibrant team culture.
- Why this job: Join a dynamic team and make a real impact in finance with your data skills.
- Qualifications: Proficient in Python, SQL, and have a strong interest in 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 have grown to over 70 people and are backed by leading investors.
We are looking for a full-time data scientist to work with us in our Product Development team. You will be working to create and maintain new KPI trackers. For example, estimating the daily revenue of an e-commerce company, or predicting the number of cars produced by an automotive manufacturer. 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 Power BI.
- 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 - Finance Focus, Time-Series & Power BI employer: Oxford Data Plan
Contact Detail:
Oxford Data Plan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Finance Focus, Time-Series & Power BI
✨Tip Number 1
Network like a pro! Reach out to people in the finance and data science sectors on LinkedIn. Join relevant groups, attend webinars, and don’t be shy about asking for informational interviews. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data visualisations and models. Use platforms like GitHub to share your projects. This not only demonstrates your expertise but also gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with Python, Power BI, and AWS. Practice explaining your thought process when solving problems, as this will show your analytical abilities and how you approach challenges.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate individuals who want to make an impact. Tailor your application to highlight your interest in finance and data science, and let us know how you can contribute to our team!
We think you need these skills to ace Data Scientist - Finance Focus, Time-Series & Power BI
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match our job description. Highlight your proficiency in Python, data visualisation, and any relevant finance experience. We want to see how you can contribute to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data science and finance, and explain why you're excited about working with us at Oxford Data Plan. Be genuine and let your personality come through.
Showcase Your Projects: If you've worked on any relevant projects, especially those involving time-series modelling or Power BI, make sure to mention them. We love seeing practical applications of your skills, so don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Oxford Data Plan
✨Know Your Data Science Stuff
Make sure you brush up on your Python skills and the key libraries like pandas, numpy, and scikit-learn. Be ready to discuss your experience with time-series modelling and how you've applied statistical concepts in real-world scenarios.
✨Show Off Your Visualisation Skills
Since the role involves creating dashboards with Power BI, prepare a few examples of your previous work. If you can, bring along some visualisations that demonstrate your ability to convey complex data insights clearly and effectively.
✨Understand the Finance Sector
Familiarise yourself with the finance industry and the types of data that are valuable for investors. Being able to discuss how your skills can help improve KPI tracking or revenue predictions will show you're genuinely interested in the role.
✨Be Ready for Problem-Solving Questions
Expect to tackle some problem-solving scenarios during the interview. Think about past challenges you've faced in data science and how you approached them. This will highlight your analytical thinking and judgement skills, which are crucial for this position.