At a Glance
- Tasks: Build real-time machine learning solutions to combat financial crime and enhance risk mitigation.
- Company: Join Tide, a leading fintech transforming small business banking for over 1.8 million members globally.
- Benefits: Enjoy competitive salary, generous leave, health insurance, and opportunities for personal development.
- Other info: Flexible work model, commitment to diversity, and excellent career growth opportunities.
- Why this job: Make a real impact in the fintech space while working with cutting-edge technology and diverse teams.
- Qualifications: 6+ years in software development or machine learning, strong Python skills, and experience with big data technologies.
The predicted salary is between 60000 - 80000 £ per year.
At Tide we help SMEs save time (and money) in the running of their businesses by not only offering business accounts and related banking services, but also a comprehensive set of highly usable and connected administrative solutions from invoicing to accounting. Tide is transforming the small business banking market with over 1.8 million members globally across the UK, India, Germany and France. Using advanced technology, all solutions are designed with SMEs in mind. With quick onboarding, low fees and innovative features, we thrive on making data-driven decisions to serve our mission: to help SMEs save both time (and money) so they can get back to doing what they love.
ABOUT THE ROLE
You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment. You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.
As a Senior Data Scientist you’ll be:
- Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
- Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
- Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
- Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
- Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
- Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
- Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
- Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.
WHAT ARE WE LOOKING FOR
You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment. You are strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statsmodels, TensorFlow, Keras, or PyTorch). You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred. You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms. You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings. You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.). You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data. Familiarity with Financial Services and Fintech space is preferred.
Highly Desirable Skills
- Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
- A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
- Experience with Drift monitoring tools and frameworks.
- Exposure to Knowledge Graphs or graph database applications.
WHAT YOU’LL GET IN RETURN:
- Competitive Compensation: competitive salary and share options.
- Time Off: Generous annual leave on top of bank holidays.
- Parental Leave: Paid maternity, paternity, and adoption leave to support your family journey.
- Sabbatical: Extended unpaid and paid leave options after completing milestone years with Tide.
- Health Insurance: Private family insurance with additional OPD coverage and top-up options.
- Life & Accident Cover: Comprehensive accidental and life insurance protection.
- Mental Wellbeing: Access to therapy sessions, courses, meditations, and workshops.
- Volunteering & Development Days: Paid days annually for volunteering or personal growth.
- Learning & Development: Annual budget for books, courses, coaching, and more.
- Work Outside the Office: Work from abroad for up to 90 days annually.
- Home Office Setup: Contribution towards setting up your home office.
- Laptop Ownership: Keep your old laptop and get a new one when it’s time for a replacement.
- Snacks & Meals: Office perks with snacks, coffee, tea, and lunch (location dependent).
TIDEAN WAYS OF WORKING
At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.
TIDE IS A PLACE FOR EVERYONE
At Tide, we believe that we can only succeed if we let our differences enrich our culture. Our Tideans come from a variety of backgrounds and experience levels. We consider everyone irrespective of their ethnicity, religion, sexual orientation, gender identity, family or parental status, national origin, veteran, neurodiversity or differently-abled status. We celebrate diversity in our workforce as a cornerstone of our success. Our commitment to a broad spectrum of ideas and backgrounds is what enables us to build products that resonate with our members’ diverse needs and lives. We are One Team and foster a transparent and inclusive environment, where everyone’s voice is heard. At Tide, we thrive on diversity, embracing various backgrounds and experiences. We welcome all individuals regardless of ethnicity, religion, sexual orientation, gender identity, or disability. Our inclusive culture is key to our success, helping us build products that meet our members' diverse needs. We are One Team, committed to transparency and ensuring everyone’s voice is heard.
Senior Data Scientist employer: Tide
At Tide, we pride ourselves on being an exceptional employer, offering a dynamic work culture that champions flexibility and inclusivity. Our commitment to employee growth is evident through generous learning budgets, volunteering days, and comprehensive health benefits, all designed to support our diverse team of Tideans. Located in the heart of Central London, we provide a vibrant environment where innovation thrives, making it an ideal place for passionate professionals to make a meaningful impact in the fintech space.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current or former Tide employees on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your machine learning knowledge. Be ready to discuss your past projects and how you've tackled complex data problems. Show us your passion for data science!
✨Tip Number 3
Don’t just focus on technical skills; highlight your soft skills too! Communication and teamwork are key at Tide, so be sure to share examples of how you've collaborated effectively in the past.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in being part of the Tide team. Let’s make it happen!
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience with machine learning, Python, and any relevant big-data technologies. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about combating financial crime and how your experience can help us at Tide. Keep it engaging and relevant to the role.
Showcase Your Projects:If you've worked on any interesting projects or have experience with MLOps, make sure to mention them! We love seeing practical examples of your work, especially if they relate to real-time ML solutions.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen on joining the Tide team!
How to prepare for a job interview at Tide
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning algorithms and statistical modelling techniques. Be ready to discuss your experience with tools like Python, TensorFlow, and Spark, as well as how you've applied them in real-world scenarios, especially in fraud detection.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of complex problems you've solved using data science. Highlight your approach to handling imbalanced datasets and how you’ve developed models that adapt to evolving threats. This will demonstrate your ability to think critically and creatively.
✨Understand the Business Context
Familiarise yourself with Tide's mission and the SME landscape. Be prepared to discuss how your work can directly impact their goals of saving time and money for small businesses. Showing that you understand the business side will set you apart from other candidates.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the technologies they use, and how they measure success in the Risk & Fraud Team. This not only shows your interest but also helps you gauge if the company culture aligns with your values.