At a Glance
- Tasks: Design and deliver data science solutions to tackle real-world business challenges.
- Company: Join a growing data science team in a dynamic environment.
- Benefits: Competitive salary, learning opportunities, and collaborative culture.
- Other info: Work on diverse projects and learn from seasoned data scientists.
- Why this job: Make a real impact by solving meaningful data problems with experienced professionals.
- Qualifications: 2-3 years' experience in Data Science and strong Python skills required.
The predicted salary is between 35000 - 45000 £ per year.
We're looking for a Data Scientist with circa 2-3 years' experience to join a growing data science team. This is a hands‑on role where you'll apply your skills to real‑world problems, working alongside experienced practitioners and contributing to meaningful, production‑focused work.
What you’ll be doing:
- Designing and delivering data science solutions to solve business problems
- Applying statistical and analytical techniques to explore data and test hypotheses
- Writing and maintaining Python code for data processing, analysis and modelling
- Working with real‑world datasets (cleaning, validation and exploration)
- Contributing to data pipelines and supporting data engineering tasks
- Collaborating with senior data scientists and engineers across multiple projects
- Communicating insights clearly to technical and non‑technical stakeholders
- Supporting responsible, ethical and compliant use of data
What we’re looking for:
- ~2-3 years' experience in Data Science or a similar analytical role
- Strong Python skills and experience working in shared codebases
- Experience with data science / ML frameworks
- Solid understanding of data preparation, analysis and modelling
- Ability to translate data insights into practical outcomes
- Strong communication and collaboration skills
- Curious mindset with a willingness to learn and challenge assumptions
Nice to have:
- Experience with Docker / containerised environments
- Experience working in product or engineering‑led teams
- Work on real, impactful data problems (not just experimentation)
- Learn from experienced data scientists in a collaborative environment
- Exposure to varied projects and modern data practices.
Associate Data Scientist employer: Lorien
Join a dynamic and innovative data science team where your contributions will directly impact real-world business challenges. We foster a collaborative work culture that prioritises continuous learning and professional growth, offering you the chance to work alongside seasoned experts while engaging with diverse projects. Located in a vibrant area, our company provides a supportive environment that values ethical data practices and encourages open communication across all levels.
StudySmarter Expert Advice🤫
We think this is how you could land Associate Data Scientist
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field and let them know you're on the lookout for opportunities. You never know who might have a lead or can refer you to a position that’s not even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and real-world datasets. This will give potential employers a taste of what you can do and how you tackle data problems.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and practising common data science questions. Be ready to discuss your past experiences and how they relate to the role you’re applying for. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications directly from candidates who are eager to join our team. Plus, it shows your enthusiasm for working with us at StudySmarter.
We think you need these skills to ace Associate Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Associate Data Scientist role. Highlight your 2-3 years of experience, especially any hands-on projects where you've applied statistical techniques or worked with Python. We want to see how your skills match what we're looking for!
Showcase Your Projects:Include specific examples of data science solutions you've designed and delivered. If you've worked on real-world datasets or contributed to data pipelines, let us know! This will help us understand your practical experience and how you can contribute to our team.
Communicate Clearly:When writing your application, keep it clear and concise. Remember, we need to see how you can communicate insights to both technical and non-technical stakeholders. Use straightforward language and avoid jargon where possible.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it shows you're keen on joining the StudySmarter team!
How to prepare for a job interview at Lorien
✨Know Your Python Inside Out
Since strong Python skills are a must for this role, make sure you brush up on your coding abilities. Be prepared to discuss your experience with Python in detail, and maybe even solve a coding challenge during the interview. Practising common data manipulation tasks can really help you shine.
✨Showcase Your Data Science Projects
Bring examples of your previous work to the table. Whether it's a project where you applied statistical techniques or a real-world dataset you cleaned and analysed, having tangible examples will demonstrate your hands-on experience. Be ready to explain your thought process and the impact of your work.
✨Communicate Like a Pro
You’ll need to communicate insights to both technical and non-technical stakeholders, so practice explaining complex concepts in simple terms. Think about how you would present your findings to someone without a data background. Clear communication can set you apart from other candidates.
✨Embrace Curiosity and Learning
This role values a curious mindset, so be prepared to discuss how you've challenged assumptions in your past work. Share examples of how you've approached learning new tools or techniques, and express your enthusiasm for continuous improvement. This attitude will resonate well with the interviewers.
