Growth Data Scientist - End-to-End Funnel, London

Growth Data Scientist - End-to-End Funnel, London

Full-Time 60750 - 74250 £ / year (est.) No working from home possible
Lovable

At a Glance

  • Tasks: Own the growth funnel from acquisition to retention, driving impactful experiments.
  • Company: Lovable, a dynamic company in London focused on growth and innovation.
  • Benefits: Competitive salary, flexible working hours, and opportunities for professional development.
  • Other info: Join a collaborative team and shape the future of Lovable's growth.
  • Why this job: Be the first data scientist in London and make a real impact on growth strategies.
  • Qualifications: Strong skills in SQL, Python, and statistics; experience in designing experiments.

The predicted salary is between 60750 - 74250 £ per year.

Lovable in London is seeking a growth-minded data scientist to own the growth funnel end-to-end, from acquisition to activation to retention to expansion.

You will partner with growth engineers to ship experiments and drive the metrics, not just analysis.

You’ll apply strong SQL, Python, and statistics, design and run experiments, and build the instrumentation and data surface Lovable needs to grow.

This is the first data scientist role in the London team.

#J-18808-Ljbffr

Growth Data Scientist - End-to-End Funnel, London employer: Lovable

At Lovable, we pride ourselves on being an exceptional employer that fosters a culture of extreme ownership and collaboration. Based in the vibrant city of Stockholm, we offer our team members the chance to work at the cutting edge of AI software creation, with ample opportunities for personal and professional growth. Join us to be part of a small, talented team where your contributions will directly impact millions of users worldwide, all while enjoying a fast-paced and innovative work environment.

Lovable

Contact Details:

Lovable Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Growth Data Scientist - End-to-End Funnel, London

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Lovable!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Growth Data Scientist - End-to-End Funnel, London at Lovable.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Lovable.

Apply Directly through Our Website

When you find a suitable opening like Growth Data Scientist - End-to-End Funnel, London at Lovable, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Growth Data Scientist - End-to-End Funnel, London

Python
SQL
Problem-Solving Skills
Communication Skills
Automation
Data Engineering
Attention to Detail

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Lovable, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Lovable. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Lovable

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Lovable!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.