At a Glance
- Tasks: Lead data science strategy for innovative non-lending products like car insurance.
- Company: Join a fast-growing fintech company revolutionising credit and savings.
- Benefits: Flexible working, health coverage, retirement plans, and tasty office meals.
- Other info: Be part of a winning team with excellent career growth opportunities.
- Why this job: Make a real impact in the fintech space with cutting-edge technology.
- Qualifications: Proven experience in data science, financial services knowledge, and strong technical skills.
The predicted salary is between 70000 - 90000 £ per year.
Lendable is on a mission to build the world's best technology to help people get credit and save money. We're building one of the world’s leading fintech companies and are off to a strong start, among the fastest-growing tech companies in the UK.
So far, we’ve rebuilt the Big Three consumer finance products from scratch: loans, credit cards, and car finance. We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes.
We are looking for the first data scientist to own the data science strategy for non-lending products. You will partner with the managing directors to define what to build from a data science perspective and lead the delivery of the data science projects. Car Insurance is our first venture into non-lending products, presenting a sophisticated new domain for our data strategy.
You are able to think strategically about commercial products and how decisions using data can unlock more value for our customers. You will directly report to the Head of Data Science (Catherine Chen) who is managing the data science team.
- Own the data science roadmap to contribute to new product expansion.
- Gather requirements internally and externally to define the success of the data science projects.
- Drive exciting data science projects from both strategic level and tactical level.
- Be a great mentor to a team of talented data scientists and the broader analytics community.
Successful track record of managing data science projects, with cross-functional teams and senior stakeholders.
Extensive knowledge of the financial services industry, including the products, data, typical ML applications, and related regulations.
Excellent technical skills in Python, SQL, and statistics.
Hands-on experience across the model lifecycle from scoping and model development to deployment and monitoring.
Experience of working in insurance, telco or consulting in financial services industry.
Final interviews with Head of Data Science and Chief Risk Officer.
Winning team: the opportunity to scale up one of the world’s most successful fintech companies.
- Flexible working: flexible approach tailored to each role. Hybrid roles require three days in-office weekly; fully remote roles include regular opportunities for in-person connection through socials and off-sites.
- Socials & connection: opportunities and events to come together, socialise, and get to know each other beyond the office walls.
- Health coverage: support for your physical and mental wellbeing, including private health cover.
- Retirement & savings: long-term financial wellbeing through retirement savings plans.
- Employee referral programme: earn a competitive bonus when you refer successful new team members.
- Office meals & snacks: enjoy a fully stocked kitchen, plus complimentary lunches prepared by in-house chefs on in-office days at select locations.
- Sustainable commuting: cycle-to-work and electric vehicle salary sacrifice schemes available in select locations.
For more information, please speak to your Talent Partner.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist - Full Time 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 Lendable!
✨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 Lead Data Scientist - Full Time at Lendable.
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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 Lendable.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Scientist - Full Time at Lendable, 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 Lead Data Scientist - Full Time 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 Lendable, 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 Lendable. 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 Lendable
✨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 Lendable!
✨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.
