Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Analyze large datasets, build machine learning models, and create impactful dashboards.
- Company: Join a dynamic London-based team focused on innovative data science projects.
- Benefits: Enjoy hybrid working, professional development, and access to cutting-edge tools.
- Why this job: Perfect for STEM grads eager to make data-driven decisions and collaborate across teams.
- Qualifications: STEM degree from a Russell Group university; proficiency in Python and SQL required.
- Other info: Stay ahead with the latest in AI and machine learning while enjoying a flexible work environment.
The predicted salary is between 28000 - 36000 £ per year.
Job Description
Graduate Data Scientist
Location: London, UK (Hybrid Working)
Salary: £35,000 – £45,000
Are you a recent STEM graduate with strong analytical skills and a passion for data science? We are looking for a Junior Data Scientist to join our clients London-based team, where you will work on complex datasets, develop predictive models, and contribute to data-driven decision-making across the business.
Key Responsibilities
- Data Analysis & Modelling: Work with large datasets to identify patterns, build machine learning models, and support business strategy.
- Algorithm Development: Develop and optimise algorithms to enhance operational efficiency and decision-making.
- Collaboration: Work closely with teams across product, operations, and technology to integrate data-driven insights.
- Data Visualisation: Create dashboards and reports to communicate findings to both technical and non-technical stakeholders.
- Research & Innovation: Stay up to date with the latest developments in data science, AI, and machine learning.
Skills & Experience Required
- A STEM degree (e.g. Mathematics, Statistics, Computer Science, Engineering) from a Russell Group university .
- Proficiency in Python and SQL for data manipulation, analysis, and model development.
- A strong understanding of machine learning concepts , including supervised and unsupervised learning techniques.
- Experience with data visualisation tools such as Tableau or Power BI.
- Strong analytical and problem-solving skills, with the ability to communicate complex findings clearly.
Desirable Skills
- Knowledge of advanced machine learning techniques , including NLP, large models (LLMs), or time series forecasting.
- Experience working with AI concepts and libraries such as Pandas, NumPy, TensorFlow, or PyTorch.
- Familiarity with cloud platforms (AWS, GCP, or Azure).
- Understanding of computer vision and deep learning techniques.
What’s on offer
- Professional Development: Clear career progression with opportunities to develop expertise in data science and machine learning.
- Innovative Work Environment: A collaborative team working on cutting-edge data science projects.
- Technical Resources: Access to industry-leading tools and platforms.
- Flexible Working: Hybrid working model with a London-based office.
To apply, please submit your CV. Successful candidates will be contacted to discuss the next steps.
#J-18808-Ljbffr
Graduate Data Scientist employer: ZipRecruiter
Contact Detail:
ZipRecruiter Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graduate Data Scientist
✨Tip Number 1
Make sure to showcase your analytical skills during the interview. Prepare examples of how you've worked with large datasets or built predictive models in your academic projects or internships.
✨Tip Number 2
Familiarize yourself with the latest trends in data science and machine learning. Being able to discuss recent advancements or tools can demonstrate your passion and commitment to the field.
✨Tip Number 3
Practice explaining complex data concepts in simple terms. Since you'll be communicating findings to both technical and non-technical stakeholders, being able to articulate your insights clearly is crucial.
✨Tip Number 4
Network with professionals in the data science community. Attend meetups or webinars to connect with others in the field, which can provide valuable insights and potentially lead to referrals.
We think you need these skills to ace Graduate Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your STEM degree and relevant skills in Python, SQL, and machine learning. Emphasize any projects or experiences that demonstrate your analytical abilities and familiarity with data visualization tools.
Showcase Relevant Experience: Include specific examples of your experience with data analysis, algorithm development, and collaboration on projects. If you have worked with large datasets or developed predictive models, be sure to mention these experiences.
Highlight Soft Skills: In addition to technical skills, emphasize your strong analytical and problem-solving skills. Mention your ability to communicate complex findings clearly, as this is crucial for working with both technical and non-technical stakeholders.
Express Your Passion: Convey your enthusiasm for data science and your commitment to staying updated with the latest developments in the field. This can set you apart from other candidates and show your potential for growth within the company.
How to prepare for a job interview at ZipRecruiter
✨Showcase Your Analytical Skills
Be prepared to discuss specific examples from your academic projects or internships where you analyzed complex datasets. Highlight your problem-solving approach and the impact of your findings.
✨Demonstrate Technical Proficiency
Make sure to brush up on your Python and SQL skills. You might be asked to solve a coding challenge or explain how you've used these tools in past projects, so be ready to dive into technical details.
✨Communicate Clearly
Since you'll be working with both technical and non-technical stakeholders, practice explaining your data findings in simple terms. Use visual aids if possible to demonstrate your ability to create dashboards and reports.
✨Stay Updated on Industry Trends
Research the latest developments in data science, AI, and machine learning. Being able to discuss recent advancements or tools will show your passion for the field and your commitment to continuous learning.
