At a Glance
- Tasks: Design and build data pipelines, analyse data, and communicate findings to stakeholders.
- Company: Join a forward-thinking research team in the finance sector.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Ideal for curious minds eager to learn and grow in a dynamic environment.
- Why this job: Make an impact by transforming data into actionable insights in equity markets.
- Qualifications: Proficient in Python and data analysis; strong analytical and communication skills.
The predicted salary is between 45000 - 55000 £ per year.
We are looking for an intellectually curious Data Scientist to join our research team on a full-time, permanent basis. You will own the design and operation of data pipelines that collect, clean, model, and evaluate alternative data sources with relevance to equity markets. The work sits at the intersection of statistical analysis, financial research, and data engineering. Expect equal parts building robust pipelines, applying rigorous quantitative methods, and communicating findings clearly to stakeholders across the business.
What You'll Do
- Design, build, and maintain web scrapers to collect structured and unstructured data from public sources.
- Clean, normalise, and validate incoming datasets; flag anomalies and document methodology.
- Evaluate data quality and relevance by assessing coverage, timeliness, and signal potential against equity market use cases.
- Conduct desk research on companies, sectors, and market themes to provide context for quantitative findings.
- Produce clear, concise written and visual outputs that communicate data findings and statistical conclusions to both technical and non-technical audiences.
- Partner with strategic managers and senior researchers to iterate on data strategies, prioritise new sources, and translate quantitative findings into actionable insights.
What We're Looking For
Must Have
- Proficiency in Python, particularly writing clean, well-structured scripts independently.
- Hands‑on experience with pandas for data manipulation, transformation, and analysis; this is a core part of day‑to‑day work.
- Strong analytical mindset: you ask good questions of data and don’t take outputs at face value.
- Attention to detail and a methodical approach to quality‑checking your own work.
- Statistical proficiency: comfortable with hypothesis testing, regression, distributions, and interpreting model outputs with appropriate rigour.
- Proven ability to present data findings to non‑technical audiences: translating complex analysis into clear narratives and actionable recommendations for business stakeholders.
- Clear written and verbal communication, with the confidence to present findings independently.
Nice to Have
- Prior exposure to equity markets, whether through professional experience, personal investing, or independent research.
- Exposure to AWS cloud services, particularly S3 for data storage or Athena for querying large datasets.
- Familiarity with SQL or basic database querying.
- Exposure to financial data providers (Bloomberg, Refinitiv, etc.) or alternative data concepts.
- Experience with version control (Git) and working in a collaborative codebase.
About You
You are a practising data scientist with demonstrable experience applying statistical methods and building data pipelines in a professional setting. A degree in data science, statistics, mathematics, economics, or a related quantitative field is preferred, but we are open to all backgrounds provided you have the skills and the drive to keep learning. If you have a genuine curiosity about markets and a talent for turning messy data into actionable insights, we want to hear from you.
Data Scientist - Research employer: Oxford Data Plan Ltd
Join a forward-thinking research team where your intellectual curiosity and data expertise will be valued. We offer a collaborative work culture that encourages continuous learning and professional growth, alongside competitive benefits tailored to support your well-being. Located in a vibrant area, our company provides unique opportunities to engage with equity markets while working on impactful projects that drive real business insights.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - Research
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. 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 projects, especially those involving Python and pandas. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your statistical knowledge and data pipeline design. Be ready to discuss your past projects and how you tackled challenges—this is your chance to shine!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Data Scientist - Research
Some tips for your application 🫡
Show Your Curiosity:We want to see your intellectual curiosity shine through in your application. Share examples of how you've explored data or tackled complex problems in the past. This will help us understand your passion for data science and research.
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate well-structured narratives that communicate your skills and experiences without unnecessary fluff. Remember, we’re looking for clarity in both your writing and your data findings!
Highlight Relevant Skills:Make sure to emphasise your proficiency in Python and experience with data manipulation tools like pandas. We want to know how you’ve used these skills in real-world scenarios, so don’t hold back on the details!
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 shows us you’re keen to join the StudySmarter team!
How to prepare for a job interview at Oxford Data Plan Ltd
✨Know Your Data Tools
Make sure you brush up on your Python skills, especially with pandas. Be ready to discuss how you've used these tools in past projects, and maybe even prepare a few examples of scripts you've written. This will show that you're not just familiar with the tools but can also apply them effectively.
✨Showcase Your Analytical Mindset
Prepare to demonstrate your analytical thinking during the interview. Think of specific instances where you questioned data outputs or identified anomalies. This will highlight your attention to detail and methodical approach, which are crucial for the role.
✨Communicate Clearly
Practice explaining complex data findings in simple terms. You might be asked to present a past project or analysis, so focus on how you can translate technical jargon into clear narratives that non-technical stakeholders can understand. This skill is key for success in the role.
✨Research the Company and Market
Before the interview, do some homework on the company and its position in the equity markets. Familiarise yourself with recent trends and data sources relevant to their work. This will not only help you answer questions more effectively but also show your genuine interest in the role and the industry.
