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For Companies At a Glance
- Tasks: Develop and maintain data science solutions using Python to solve real business problems.
- Company: Join a collaborative, people-first culture in a dynamic Nottingham-based team.
- Benefits: Enjoy hybrid working, 25 days holiday, yearly bonuses, and a contributory pension scheme.
- Other info: Flexible work pattern with opportunities for continuous improvement and career growth.
- Why this job: Make an impact with award-winning ML models while growing your data science skills.
- Qualifications: 3+ years as a data scientist with strong Python and SQL skills.
The predicted salary is between 60000 - 60000 £ per year.
Location – Nottingham
Work pattern – Hybrid – 2 times a month in the office.
Salary – Up to £60,000
The Opportunity
We are seeking a mid-level Data Scientist with strong experience in Python for a new role in Nottingham. You will be part of a small, but close team that covers Data Science, Business Intelligence and Analytics. It is hybrid, 2 days a month in the office (so very flexible), but we are looking for someone with a sensible commute to Nottingham.
The Role
In this position you will work across a range of analytical and machine learning tasks, partnering with stakeholders to solve real business problems and support data-driven decision-making. The business has 4-6 ML models in production, one of which is award-winning. Generally, these models are in the finance and risk areas – any experience of this would be a bonus, but certainly not essential. In addition, they have a number of side projects for you to get involved with, working with colleagues to deliver advanced analytics and insights. This is a perfect role for someone who can engage confidently with stakeholders, work both independently and within a small team on defined analytical problems, can clearly communicate insights, and is comfortable contributing to production-ready data science solutions.
Role Responsibilities:
- Develop, test, and maintain data science solutions using Python
- Perform exploratory data analysis (EDA) to identify trends, patterns, and opportunities
- Apply statistical and machine learning techniques to address business questions
- Use segmentation and clustering techniques where appropriate to support insight generation
- Interpret model results and communicate insights clearly to technical and non-technical audiences
- Support model validation, documentation, and ongoing monitoring
- Contribute to continuous improvement of data science standards, tools, and ways of working
Requirements:
- 3 plus years in industry as a data scientist
- Strong Python proficiency, including a solid understanding of statistics and machine learning fundamentals
- Experience working with structured data and SQL
- Ability to communicate analytical findings clearly and confidently
- Experience supporting machine learning models in production environments
Benefits:
- Collaborative, people-first culture
- Hybrid working arrangements (requirement to travel to the office 2 days per month)
- 25 days holiday + bank holidays
- Yearly bonus scheme
- Contributory Pension scheme
Data Scientist employer: Oscar
Contact Detail:
Oscar Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or attend industry meetups. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Prepare for those interviews by brushing up on your Python skills and machine learning concepts. We recommend doing mock interviews with friends or using online platforms to get comfortable with common questions.
✨Tip Number 3
Showcase your projects! Whether it's through a portfolio or GitHub, having tangible examples of your work can really impress potential employers. Make sure to highlight any experience with ML models, especially if they relate to finance or risk.
✨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 proactive about their job search!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your Python skills and any experience with machine learning models, especially if you've worked in finance or risk. We want to see how your background fits with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to our team. Be sure to mention your experience with stakeholder engagement and communication, as these are key for us.
Showcase Your Projects: If you've worked on any relevant projects, whether in a professional setting or as side projects, make sure to include them. We love seeing practical applications of your skills, so don't hold back on sharing your successes and learnings!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Plus, it's super easy!
How to prepare for a job interview at Oscar
✨Know Your Python Inside Out
Since the role requires strong experience in Python, make sure you brush up on your skills. Be prepared to discuss specific projects where you've used Python for data science tasks, and be ready to solve coding challenges on the spot.
✨Showcase Your Analytical Mindset
Prepare to talk about your experience with exploratory data analysis (EDA) and how you've identified trends or patterns in past projects. Use concrete examples to demonstrate your ability to apply statistical and machine learning techniques to real business problems.
✨Communicate Like a Pro
This role involves engaging with stakeholders, so practice explaining complex concepts in simple terms. Think of ways to present your insights clearly to both technical and non-technical audiences, as this will be crucial during the interview.
✨Be Ready for Real-World Scenarios
Expect questions that assess your problem-solving skills in practical situations. Prepare to discuss how you've contributed to production-ready data science solutions and how you handle model validation and monitoring in your previous roles.