At a Glance
- Tasks: Design and deliver data science solutions to tackle real business challenges.
- Company: Join a growing data science team in a vibrant London setting.
- Benefits: Gain hands-on experience, learn from experts, and work on impactful projects.
- Other info: Opportunity to work on varied projects and enhance your career in data science.
- Why this job: Make a difference with your data skills while developing in a collaborative environment.
- Qualifications: 2-3 years in Data Science, strong Python skills, and a passion for analytics.
The predicted salary is between 35000 - 42000 £ per year.
We're looking for a Data Scientist with circa 2-3 years' experience to join a growing data science team.
- 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
- Contributing to data pipelines and supporting data engineering tasks
- Collaborating with senior data scientists and engineers across multiple projects
- Supporting responsible, ethical and compliant use of data
Requirements:
- 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
- Understanding of data engineering workflows
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. If you're an early-career Data Scientist looking to develop your skills on meaningful work, apply now.
Associate, Data Scientist in London employer: Lorien
Join our dynamic data science team in London, where you'll have the opportunity to work on impactful projects that drive real business solutions. We foster a collaborative and inclusive work culture, offering continuous learning and growth opportunities alongside experienced professionals. With a focus on ethical data use and innovative practices, we provide a supportive environment for early-career Data Scientists to thrive and make a difference.
StudySmarter Expert Advice🤫
We think this is how you could land Associate, Data Scientist in London
✨Embrace Online Competitions
Get involved in online data science competitions like Kaggle or DrivenData. These platforms not only let you showcase your skills but also help you build a portfolio that stands out to hiring companies like Lorien when you're aiming for that entry-level role.
✨Join Data Science Meetups
Look for local data science meetups or workshops happening in your area. These are perfect for connecting with industry professionals and fellow newbies, giving us the chance to learn the ropes and get our foot in the door at companies like Lorien.
✨Networking Through University Career Services
Don't forget to leverage your university's career services! They often have exclusive internships and networking events specifically for entry-level data science positions. This is a golden opportunity to meet recruiters from companies like Lorien.
✨Spotlight Your Skills Online
Create a strong online presence by sharing your projects and insights on platforms like GitHub or LinkedIn. Make sure to apply directly through Lorien’s career page, where your unique skills can shine in their entry-level data science openings!
We think you need these skills to ace Associate, Data Scientist in London
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at Lorien, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at Lorien aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
Show Your Curiosity:In the data science world, curiosity is key! Mention any online courses or certifications you've pursued that complement your studies. This could be anything from a statistics certification to a data visualisation workshop. It shows us you're serious about learning and growing in this field.
How to prepare for a job interview at Lorien
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
