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For Companies At a Glance
- Tasks: Develop and refine KPI prediction models using real-world data.
- Company: Join a rapidly growing UK-based start-up specialising in predictive analytics.
- Benefits: Enjoy remote work flexibility and a competitive salary of up to £45,000.
- Why this job: Make a real impact by empowering investors with actionable insights.
- Qualifications: 1-2 years in data science or a Master’s degree; strong Python skills required.
- Other info: Engage in a hands-on data task and a technical interview with the Head of Technology.
The predicted salary is between 36000 - 54000 £ per year.
This UK-based start-up has grown rapidly in just two years. With a team of ~30 people, they are scaling quickly, supported by recent funding and a strong growth pipeline. They specialise in predictive analytics, tracking KPIs for a wide range of companies and industries. Their insights empower investors to make informed decisions by providing performance data ahead of public reports.
As a Data Scientist, you’ll play a pivotal role in developing and refining KPI prediction models, working with real-world data to create actionable insights.
- Clean and process data to ensure accuracy and usability.
- Build and maintain linear regression models for KPI tracking.
- Access APIs and integrate software tools to enhance workflows.
- Collaborate with the revenue team to generate insightful reports.
- Support internal product development by improving data pipelines and analysis.
What They’re Looking For:
- 1-2 years in data science or a related field, or a Master’s degree.
- Strong Python programming (essential), SQL, and linear regression/statistical modeling. Experience with web scraping, machine learning, or dashboarding is a plus.
- A background in finance or exposure to financial data is advantageous but not required.
The Process:
- A data task: Process raw data and build a model to predict revenue (2-4 hours).
- A technical interview with the Head of Technology, covering coding, statistics, and technical problem-solving.
Data Scientist employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Brush up on your Python skills, especially focusing on libraries like Pandas and NumPy. Being proficient in these will not only help you with the data task but also impress during the technical interview.
✨Tip Number 2
Familiarise yourself with linear regression models and their applications in KPI tracking. Understanding how to build and interpret these models will be crucial for the role and can set you apart from other candidates.
✨Tip Number 3
Practice processing raw data and creating predictive models. You might want to simulate the data task they require by using datasets available online to showcase your skills effectively.
✨Tip Number 4
Prepare for the technical interview by reviewing common coding challenges and statistical problems. This will help you feel more confident and ready to tackle any questions that come your way.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly focusing on your skills in Python, SQL, and regression models. Include any projects or tasks that demonstrate your ability to work with real-world data.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention specific experiences that align with their needs, such as your familiarity with predictive analytics or any relevant projects you've completed.
Showcase Your Technical Skills: Prepare to discuss your technical skills in detail. Be ready to provide examples of how you've used Python and SQL in past projects, and consider including links to any relevant work or GitHub repositories.
Prepare for the Data Task: Before the interview, practice processing raw data and building models. Familiarise yourself with common data tasks and ensure you can demonstrate your problem-solving skills effectively during the technical interview.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in Python and SQL during the interview. Be prepared to discuss specific projects where you've used these skills, especially in building regression models or working with real-world data.
✨Prepare for the Data Task
Before the interview, practice processing raw data and building predictive models. Familiarise yourself with common datasets and try to replicate similar tasks to ensure you're comfortable with the process.
✨Understand the Company’s Focus
Research the company’s work in predictive analytics and KPI tracking. Being able to discuss how your skills can contribute to their goals will demonstrate your genuine interest and understanding of their business.
✨Brush Up on Statistical Concepts
Since the technical interview will cover statistics and problem-solving, review key concepts related to linear regression and statistical modelling. Be ready to explain your thought process when tackling technical problems.
