At a Glance
- Tasks: Own the growth funnel and drive impactful experiments with data.
- Company: Join Lovable, a pioneering tech company transforming software creation.
- Benefits: Competitive salary, flexible work environment, and opportunities for personal growth.
- Other info: Dynamic team culture focused on collaboration and innovation.
- Why this job: Be the first data scientist in London and shape the future of growth at Lovable.
- Qualifications: Experience in SQL, Python, and a passion for driving growth metrics.
The predicted salary is between 72000 - 88000 £ per year.
The first data scientist in our new London growth team. You own the growth funnel end to end, from acquisition to activation to retention to expansion, find the levers, and work directly with growth engineering to ship experiments into the product. Not decision support: you drive the numbers.
Why Lovable? Lovable lets anyone and everyone build software with any language. From solopreneurs to Fortune 100 teams, millions of people use Lovable to transform raw ideas into real products, fast. We are at the forefront of a foundational shift in software creation, which means you have an unprecedented opportunity to change the way the digital world works. Lovable-built applications and websites are visited hundreds of millions of times a month, and our enterprise footprint is compounding fast. And we're just getting started.
We're a small, talent-dense team building a generation-defining company from Stockholm, now growing a team in London. We value extreme ownership, high velocity, and low-ego collaboration. We seek out people who care deeply, ship fast, and are eager to make a dent in the world.
What we're looking for:
- A growth-minded data scientist who owns funnel outcomes: you find the lever, run the experiment, and drive the metric, working shoulder to shoulder with growth engineers.
- Deep instinct for acquisition, activation, retention, and expansion, and what actually moves them.
- Strong SQL, Python, applied statistics, and heavy experimentation (A/B and growth tests) in a fast-moving environment.
- You build the systems and agents that surface growth opportunities proactively, not one-off analyses.
- Comfortable shipping fast with directional reads, and knowing when rigor matters.
- Entrepreneurial and autonomous. Excited to be first in seat and shape how growth data works at Lovable.
What you'll do:
- Own the growth funnel metrics end to end and drive measurable improvement across acquisition, activation, retention, and expansion.
- Find the highest-leverage opportunities in the funnel and turn them into experiments that ship, working directly with growth engineering.
- Design, run, and read growth experiments, and act on them.
- Build the instrumentation, metrics, and agents the growth team runs on.
- Help shape the growth data function as its first data scientist.
Our tech stack:
- Languages: SQL and Python
- Warehouse & events: BigQuery, PubSub
- Analytics & product: Hex, Lovable Apps
- Experimentation: A/B and growth testing
- Cloud: GCP
- And always on the lookout for what's next.
How we hire:
- Fill in a short form and jump on an intro call with our recruiting team
- A call with the hiring manager
- A take-home case study
- A Most Impressive Project session
- Cross-functional interviews with the people you'd work with
- A final conversation with leadership
About your application: Please submit your application in English. It's our company language, so you'll be speaking lots of it if you join. We treat all candidates equally. If you're interested, please apply through our careers portal.
Data Scientist, Growth in 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.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist, Growth in 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 Data Scientist, Growth 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 Data Scientist, Growth 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 Data Scientist, Growth in London
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.
