Mid/Senior Data Scientist

Two; London; Hybrid; GBP 40,000 - 80,000; Full time

Job summary

An innovative startup is seeking a Mid or Senior-Level Data Scientist to join their dynamic team. This role focuses on leveraging data science to enhance risk management, fraud detection, and customer behavior analytics. You will apply machine learning and advanced statistical techniques to develop impactful models for a rapidly growing B2B payment platform. The company offers a flexible work environment and generous benefits, including paid time off and allowances for health and training. If you are passionate about data-driven solutions and thrive in a fast-paced setting, this opportunity is perfect for you.

Benefits

25 days paid time off

£500 annual health allowance

£500 phone allowance every 24 months

£500 annual learning allowance

Cycle to work scheme

Flexible work environment

Qualifications

• 3-5 years experience in data science or machine learning.
• Strong programming skills in Python and SQL.

Responsibilities

• Develop and deploy machine learning models for credit risk assessment.
• Analyse large datasets to drive data-informed decision-making.

Skills

Python

SQL

Machine Learning

Statistical Analysis

Data Visualization

Problem Solving

Education

Degree in Data Science

Degree in Mathematics

Degree in Computer Science

Tools

Pandas

Scikit-learn

NumPy

TensorFlow

Keras

Job description

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.

Backed by leading VCs such as Sequoia, Shine, LocalGlobe, Antler, and Posten, along with influential Fintech angel investors, we've raised over €30 million to date. Now, we're expanding our team to continue reshaping the future of B2B payments.

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:

1. Develop and deploy machine learning models to optimise credit risk assessment, fraud detection, and transaction automation
2. Analyse large datasets to extract meaningful insights and drive data-informed decision-making
3. Enhance our data pipelines and machine learning infrastructure, ensuring efficient model training and deployment
4. Collaborate with engineering, product, and risk teams to integrate data science solutions into real-time production environments
5. Conduct statistical analyses and A/B testing to validate hypotheses and improve model performance
6. Continuously research and experiment with emerging techniques in machine learning, deep learning, and data analytics

Requirements

1. 3-5 years of experience in data science, machine learning, or a related field
2. Strong programming skills in Python and SQL, with the ability to query databases and manipulate large datasets
3. Proficiency in key Python libraries for data science, including Pandas, Scikit-learn, Statsmodels, NumPy, SciPy, Matplotlib, TensorFlow, and Keras
4. Solid understanding of machine learning techniques, such as clustering, tree-based methods, boosting, text mining, and neural networks
5. Expertise in statistical modeling and techniques such as regression, hypothesis testing, simulation, resampling methods, and stratification
6. Degree in Data Science, Mathematics, Physics, Computer Science, Engineering, or another quantitative field (or equivalent experience)
7. Strong business acumen with a problem-solving mindset, ideally with experience in fintech or payments
8. Excellent communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders
9. 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