At a Glance
- Tasks: Own real-time recommendation and pricing models that directly impact revenue.
- Company: Fast-growing, profitable company with no VC backing.
- Benefits: Up to £220,000 salary, equity, bonus, and a dynamic work environment.
- Other info: Join a collaborative team shaping the future of consumer-scale ML.
- Why this job: Make a real impact on user engagement and conversion at scale.
- Qualifications: Experience with recommender systems and fluency in Python and SQL.
The predicted salary is between 70000 - 90000 £ per year.
Salary: Up to £220,000 base + equity + bonus
The role involves optimising a market with tens of millions of users earning real rewards for engaging with advertisers' products. Every ranking decision carries a price, an incentive, and a margin. Getting the models right can directly impact revenue, while getting them wrong can break the economics. This is a unique consumer-scale ML problem where ranking, pricing, and incentive design intersect within a profitable and rapidly growing company.
The work includes:
- Owning real-time recommendation, ranking, and pricing models at consumer scale, focusing on engagement and conversion as direct revenue levers.
- Designing reward and user-incentive systems that balance user motivation against sustainable ROAS through uplift modelling and pricing optimisation.
- Driving experimentation in causal impact estimation, MMM, and Multi-Touch Attribution that influence decisions.
- Taking zero-to-one bets from initial data structures to final deployment, fully owned by you.
- Shaping the stack and system architecture with engineering, defining the gold standard for a 20-person hub.
What you bring:
- Experience with recommender systems or ranking shipped in production at scale, owned end to end.
- A Staff-level operating record, setting technical direction, creating structure in ambiguity, and engaging stakeholders while still writing code.
- Fluency in Python, SQL, and the modern data stack (DBT, Airflow, Kubernetes, Terraform) on cloud, preferably GCP, ideally from gaming, adtech, or user-incentive systems.
- Eligibility to work in the UK and willingness to be on-site in London.
As part of the recruitment process at Dex, we process your personal data in accordance with our Privacy Notice for Job Applicants.
Staff Data Scientist in London employer: Dex
At Dex, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our London-based team enjoys competitive salaries, equity options, and bonuses, alongside ample opportunities for professional growth in a fast-paced environment where your contributions directly impact our success. Join us to tackle unique challenges in real-time recommendation systems while working with cutting-edge technology in a profitable, rapidly growing company that values your expertise and creativity.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Data Scientist 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 Dex!
✨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 Staff Data Scientist at Dex.
✨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 Dex.
✨Apply Directly through Our Website
When you find a suitable opening like Staff Data Scientist at Dex, 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 Staff Data Scientist 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 Dex, 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 Dex. 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 Dex
✨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 Dex!
✨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.
