Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join us as a Data Scientist to develop machine learning models and analyse data for impactful insights.
- Company: Two is an innovative startup revolutionising B2B payments with cutting-edge, data-driven solutions.
- Benefits: Enjoy 25 days off, health allowances, training budgets, and a flexible work environment.
- Why this job: Be part of a fast-paced team shaping the future of B2B payments with exciting data challenges.
- Qualifications: 3-5 years in data science, strong Python and SQL skills, and a degree in a quantitative field.
- Other info: Work closely with cross-functional teams in a dynamic startup atmosphere.
The predicted salary is between 36000 - 60000 £ per year.
Are you passionate about data-driven innovation, building best-in-class data products, and delivering impactful business insights? Do you have strong technical expertise in Python, SQL, and experience in analysing and modeling data? Are you eager to work in a fast-paced, cross-functional team within an early-stage startup, where you can take ownership and actively shape our data strategy? If so, we would love to hear from you!
At Two, we are revolutionising B2B payments by bringing the best of B2C e-commerce to the B2B world. Our innovative, data-driven solutions empower businesses to sell more, faster, and more efficiently, creating a seamless commerce experience. With an impressive 30% month-on-month growth rate, our ambition is to become the world's largest B2B payment solution by 2027.
About the role:
We are looking for a Mid or Senior-Level Data Scientist to join our high-performing team, united by a passion for data excellence. This is an exciting opportunity to work in a dynamic, fast-paced environment, where data science plays a crucial role in risk management, fraud detection, customer behavior analytics, and automation of financial processes.
In this role, you will apply machine learning, advanced statistical techniques, and large-scale data processing to develop models that enhance our BNPL platform. You will work closely with Engineering, Risk, and Product teams to deploy scalable, data-driven solutions that fuel business growth.
Key Responsibilities:
- Develop and deploy machine learning models to optimise credit risk assessment, fraud detection, and transaction automation
- Analyse large datasets to extract meaningful insights and drive data-informed decision-making
- Enhance our data pipelines and machine learning infrastructure, ensuring efficient model training and deployment
- Collaborate with engineering, product, and risk teams to integrate data science solutions into real-time production environments
- Conduct statistical analyses and A/B testing to validate hypotheses and improve model performance
- Continuously research and experiment with emerging techniques in machine learning, deep learning, and data analytics
Requirements:
- 3-5 years of experience in data science, machine learning, or a related field
- Strong programming skills in Python and SQL, with the ability to query databases and manipulate large datasets
- Proficiency in key Python libraries for data science, including Pandas, Scikit-learn, Statsmodels, NumPy, SciPy, Matplotlib, TensorFlow, and Keras
- Solid understanding of machine learning techniques, such as clustering, tree-based methods, boosting, text mining, and neural networks
- Expertise in statistical modeling and techniques such as regression, hypothesis testing, simulation, resampling methods, and stratification
- Degree in Data Science, Mathematics, Physics, Computer Science, Engineering, or another quantitative field (or equivalent experience)
- Strong business acumen with a problem-solving mindset, ideally with experience in fintech or payments
- Excellent communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders
- Ability to work in a dynamic, fast-paced environment, adapting to changing priorities and objectives
Benefits:
- 25 days paid time off per year + public holidays
- £500 annual allowance to spend on anything that will contribute to your mental or physical health
- £500 allowance towards a phone device every 24 months (from your 6th month anniversary)
- £500 annual allowance for learning and training
- Cycle to work scheme
- Enjoy a flexible work environment, balancing onsite and working from home
Mid/Senior Data Scientist employer: Two
Contact Detail:
Two Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Mid/Senior Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in data science and machine learning, especially those relevant to fintech. This will not only help you during interviews but also demonstrate your passion for the field and your commitment to staying updated.
✨Tip Number 2
Network with professionals in the fintech and data science communities. Attend meetups, webinars, or conferences where you can connect with industry experts and potentially get referrals that could lead to an interview.
✨Tip Number 3
Prepare to discuss specific projects you've worked on that showcase your skills in Python, SQL, and machine learning. Be ready to explain your thought process, the challenges you faced, and how your contributions made a difference.
✨Tip Number 4
Research Two's current data products and their impact on B2B payments. Understanding their business model and how data science fits into their strategy will allow you to tailor your discussions and show how you can contribute to their goals.
We think you need these skills to ace Mid/Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly with Python and SQL. Emphasise any projects or roles where you've developed machine learning models or worked with large datasets.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data-driven innovation and how your skills align with the company's mission. Mention specific examples of how you've contributed to data strategy in previous roles.
Showcase Technical Skills: Clearly list your technical skills, especially those mentioned in the job description, such as proficiency in Python libraries like Pandas and Scikit-learn. Provide examples of how you've applied these skills in real-world scenarios.
Highlight Collaboration Experience: Since the role involves working closely with cross-functional teams, include examples of past collaborations with engineering, product, or risk teams. This will demonstrate your ability to integrate data science solutions effectively.
How to prepare for a job interview at Two
✨Showcase Your Technical Skills
Make sure to highlight your expertise in Python and SQL during the interview. Be prepared to discuss specific projects where you've used these skills, and consider bringing examples of your work or code snippets to demonstrate your proficiency.
✨Understand the Business Context
Familiarise yourself with Two's mission and the B2B payments landscape. Being able to articulate how your data science skills can directly impact their business goals will show that you are not just technically capable but also aligned with their vision.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities, particularly in risk management and fraud detection. Practice explaining your thought process clearly and logically, as this will be crucial in demonstrating your analytical skills.
✨Communicate Effectively
Since you'll be working with cross-functional teams, it's important to convey complex technical concepts in a way that non-technical stakeholders can understand. Practice simplifying your explanations and focus on the impact of your work on the business.
