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.
- Other info: Engage in a hands-on data task and a technical interview with the Head of Technology.
- Why this job: Make a real impact by empowering investors with actionable insights and data-driven decisions.
- Qualifications: 1-2 years in data science or a Master’s degree; strong Python skills required.
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 in Liverpool employer: Harnham
Join a dynamic and forward-thinking B2B company that prioritises data-driven decision making and offers a fully remote work environment across the UK. With a strong focus on employee growth, you will have the opportunity to lead a talented team while shaping the marketing analytics strategy in a rapidly expanding organisation. Enjoy a collaborative work culture that values innovation and provides significant investment in your professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in Liverpool
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, especially Python and SQL. Consider working on personal projects or contributing to open-source projects that showcase your skills in these areas.
✨Tip Number 2
Brush up on your knowledge of linear regression and statistical modelling. You might want to review case studies or examples where these techniques have been applied in real-world scenarios, particularly in predictive analytics.
✨Tip Number 3
Prepare for the data task by practising with raw datasets. Try processing data and building models to predict outcomes, as this will help you feel more confident when tackling the task during the interview process.
✨Tip Number 4
Network with professionals in the data science field, especially those who work in predictive analytics or finance. Engaging in discussions or seeking mentorship can provide valuable insights and potentially lead to referrals.
We think you need these skills to ace Data Scientist in Liverpool
Some tips for your application 🫡
Understand the Role:Read the job description thoroughly to grasp the key responsibilities and required skills. Focus on the specific tools and techniques mentioned, such as Python programming and linear regression.
Tailor Your CV:Highlight relevant experience in data science, particularly any work with predictive analytics or KPI tracking. Make sure to include specific projects or achievements that demonstrate your skills in Python, SQL, and statistical modelling.
Craft a Compelling Cover Letter:Use your cover letter to explain why you are passionate about data science and how your background aligns with the company's goals. Mention any experience with financial data or predictive modelling to strengthen your application.
Prepare for the Data Task:Before submitting your application, practice processing raw data and building models. Familiarise yourself with common data tasks and ensure you can demonstrate your skills effectively during the technical interview.
How to prepare for a job interview at Harnham
✨Brush Up on Your Python Skills
Since strong Python programming is essential for this role, make sure to review key libraries like Pandas and NumPy. Be prepared to demonstrate your coding skills during the technical interview.
✨Understand Regression Models
Familiarise yourself with linear regression and other statistical modelling techniques. Be ready to discuss how you would apply these models to real-world data and the implications of your findings.
✨Prepare for the Data Task
The data task is a crucial part of the interview process. Practice processing raw data and building predictive models in advance. Time yourself to ensure you can complete it within the given timeframe.
✨Know the Company and Its Industry
Research the start-up's focus on predictive analytics and their target industries. Understanding their business model and how your role as a Data Scientist fits into their growth will impress your interviewers.
