At a Glance
- Tasks: Design and deploy scalable ML models for fraud prevention and operational efficiency.
- Company: Join Dojo, a game-changing payments infrastructure company with an office-first culture.
- Benefits: Competitive salary, diverse work environment, and opportunities for professional growth.
- Other info: Collaborative team focused on diversity, equity, and inclusion.
- Why this job: Make a real impact by tackling complex modeling problems and driving AI workflows.
- Qualifications: Proficiency in Python, SQL, and experience with machine learning systems.
The predicted salary is between 63000 - 77000 £ per year.
Our payments infrastructure, purpose-built for in-person commerce, is game changing.
The results take care of themselves.
The role A Machine Learning Data Scientist designs, builds, and deploys the scalable models and algorithmic systems powering Dojo's automated decisions—from fraud prevention to operational efficiency.
Where off-the-shelf scripts promise easy answers, your job is to build systems that survive production: balancing statistical rigor with clean software engineering to ensure our algorithms are robust, interpretable, and scale flawlessly.
On our Builder track, you'll focus on deep algorithmic execution, numerical optimization, and software craft.
You're the person the team turns to when a prediction or optimization problem is hard, standard machine learning isn't enough, or a model degrades in the wild.
You protect the integrity, reliability, and long-term health of our live production systems.
Drive technical projects from ideation to production, anticipating domain problems and aligning your roadmap with key commercial levers.
Tackle complex modeling problems and design end-to-end ML systems, prioritizing robustness and maintainability over over-engineering.
Build numerical optimizers (LP/MIP), tune solvers, and design custom heuristics when exact objective functions or data are scarce.
Take responsibility for live models, monitoring for drift, preventing train/serve skew, and debugging subtle mathematical failures.
Write well-structured, tested Python and SQL at scale, using Databricks and advanced data manipulation techniques.
Drive AI workflows: Safely leverage AI tools to boost development productivity, while rigorously verifying output logic and optimization reasoning.
Python & SQL craft: Mastery of Python, Databricks, and the modern ML ecosystem, combined with writing highly efficient, scalable SQL.
That's why we have an office-first culture.
This means working from the office 4+ days per week.
Our social hubs make it easy.
Diversity, equity, and inclusion at Dojo From local bakeries to well-known eateries, Dojo payments serve over 150,000 places across the UK.
And something that's fundamental to creating relevant, innovative products at Dojo is to build teams to reflect the diversity of the businesses we serve.
Our drive to improve diversity, equity, and inclusion is closely linked to helping employees thrive and innovating for better customer experiences.
To make sure you're the best you can be throughout the recruitment process, let us know if you need any extra adjustments to help you thrive.
By submitting my application I acknowledge that my personal data and all information collected will be processed in accordance with Dojo's Privacy Policy. #LI-Hybrid
Data Scientist (Python, ML, SQL) in London employer: PaymentSense
At Dojo, we pride ourselves on being an exceptional employer that values our people as our greatest asset. With an office-first culture that encourages collaboration and innovation, our employees enjoy a dynamic work environment designed for both focus and creativity. We offer robust growth opportunities, a commitment to diversity and inclusion, and the chance to be part of a game-changing team in the payments industry, all while working in vibrant office spaces across Europe.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist (Python, ML, SQL) 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 PaymentSense!
✨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 (Python, ML, SQL) at PaymentSense.
✨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 PaymentSense.
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist (Python, ML, SQL) at PaymentSense, 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 (Python, ML, SQL) 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 PaymentSense, 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 PaymentSense. 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 PaymentSense
✨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 PaymentSense!
✨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.
