Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and deploy machine learning models to solve complex business problems.
- Company: Caribou is revolutionising international tax for global businesses, making it accessible and affordable.
- Benefits: Enjoy a competitive salary, generous EMI options, health insurance, and custom WFH setups.
- Why this job: Join a dynamic team tackling real-world challenges with innovative data solutions in a supportive culture.
- Qualifications: Master’s or Ph.D. in a relevant field, plus 3+ years of experience in data science or machine learning.
- Other info: Ideal for those passionate about AI and eager to make an impact in a startup environment.
The predicted salary is between 48000 - 84000 £ per year.
About Caribou
International tax is a rigged system. Tax rules get ever-more complicated, compliance gets more expensive, and the Big Four controls the expertise. They charge fees that only giant companies can afford, while smaller businesses are left flying blind. Caribou is a tax platform designed to make international tax accessible to every global business. We’re fixing Transfer Pricing first, where one million businesses are in need, but only ten thousand experts exist. Our backers include Y Combinator, Accel, Lakestar and angel investors who were founders or executives of leading companies in London and San Francisco.
About the Role
We’re looking for a Machine Learning Data Scientist to join our team. In this role, you will design, develop, and deploy machine learning models to solve complex business problems, leveraging large datasets from customer books and accounts to generate actionable insights for our transfer pricing team. You will collaborate with tax and accounting experts within our team to identify opportunities for data-driven innovation and ensure models are scalable, accurate, and impactful.
In this role, you will:
- Work closely with our tax/accounting team to understand financial processes with our customers
- Design and implement machine learning algorithms to assist us with these processes
- Evaluate model performance using appropriate metrics and optimize for accuracy, efficiency, and scalability
- Collaborate with engineers to integrate ML models into production systems
- Conduct exploratory data analysis to uncover trends, patterns, and opportunities for improvement
- Stay current with advancements in machine learning, AI, and data science methodologies to continuously improve processes and solutions
Requirements for the role:
- Master’s or Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or a related field (Bachelor’s with significant experience also considered)
- 3+ years of experience in data science, machine learning, or a related role
- Proficiency in programming languages such as Python or R, and libraries like TensorFlow, PyTorch, Scikit-learn, or Pandas
- Strong understanding of statistical modeling, probability, and optimization techniques
- Ability to work with messy, real-world datasets and perform feature engineering
- Excellent problem-solving skills and attention to detail
- Strong communication skills to convey complex concepts to diverse audiences
Bonus points:
- You’ve worked in an early-stage startup before and understand the challenges
Perks & Benefits (for UK-based full-time employees):
- Competitive salary
- Generous EMI options
- 100% book subsidy
- Pension
- Health Insurance
- Custom WFH equipment setup
Machine Learning Data Scientist London employer: Caribou
Contact Detail:
Caribou Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Data Scientist London
✨Tip Number 1
Familiarise yourself with the specific machine learning algorithms and techniques mentioned in the job description. Being able to discuss your experience with TensorFlow, PyTorch, or Scikit-learn during an interview will show that you have the technical skills they are looking for.
✨Tip Number 2
Research Caribou's approach to international tax and transfer pricing. Understanding their mission and how your role as a Machine Learning Data Scientist can contribute to their goals will help you articulate your value during discussions.
✨Tip Number 3
Prepare examples of past projects where you've successfully implemented machine learning models. Be ready to explain the challenges you faced, how you overcame them, and the impact your work had on the business outcomes.
✨Tip Number 4
Network with professionals in the data science and tax fields. Engaging with communities on platforms like LinkedIn can provide insights into the industry and may even lead to referrals, increasing your chances of landing the job.
We think you need these skills to ace Machine Learning Data Scientist London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning and data science. Focus on projects where you've designed and deployed models, and include specific programming languages and tools you've used, such as Python, TensorFlow, or Scikit-learn.
Craft a Compelling Cover Letter: In your cover letter, express your passion for making international tax accessible and how your skills can contribute to Caribou's mission. Mention any experience you have with financial processes or working with cross-functional teams, as collaboration is key in this role.
Showcase Your Problem-Solving Skills: Provide examples of how you've tackled complex business problems using data-driven approaches. Highlight any specific metrics or outcomes that demonstrate the impact of your work, especially in relation to model performance and scalability.
Stay Current with Industry Trends: Mention any recent advancements in machine learning or data science methodologies that you've applied in your work. This shows your commitment to continuous improvement and staying updated, which is crucial for the role at Caribou.
How to prepare for a job interview at Caribou
✨Understand the Business Context
Before your interview, make sure you understand Caribou's mission and how they aim to simplify international tax. Familiarise yourself with transfer pricing and the challenges smaller businesses face in this area. This knowledge will help you demonstrate your alignment with their goals.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning algorithms and the programming languages mentioned in the job description, such as Python or R. Bring examples of past projects where you've successfully implemented models, and be ready to explain your thought process and the outcomes.
✨Prepare for Problem-Solving Questions
Expect to tackle some problem-solving scenarios during the interview. Practice explaining your approach to data analysis and model evaluation. Highlight your ability to work with messy datasets and how you would optimise models for accuracy and efficiency.
✨Communicate Clearly
Strong communication skills are essential for this role. Be ready to explain complex concepts in a way that non-technical team members can understand. Practise articulating your ideas clearly and concisely, as this will show your ability to collaborate effectively with the tax and accounting teams.
