Are you passionate about data-driven innovation,building best-in-class data products, and delivering impactfulbusiness insights? Do you have strong technical expertise inPython, SQL, and experience in analysing and modeling data? Are youeager to work in a fast-paced, cross-functional team within anearly-stage startup, where you can take ownership and activelyshape our data strategy? If so, we would love to hear from you! AtTwo, we are revolutionising B2B payments by bringing the best ofB2C e-commerce to the B2B world. Our innovative, data-drivensolutions empower businesses to sell more, faster, and moreefficiently, creating a seamless commerce experience. With animpressive 30% month-on-month growth rate, our ambition is tobecome the world’s largest B2B payment solution by 2027. Backed byleading 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 continuereshaping the future of B2B payments. About the role: We arelooking for a Mid or Senior-Level Data Scientist to join ourhigh-performing team, united by a passion for data excellence. Thisis an exciting opportunity to work in a dynamic, fast-pacedenvironment, where data science plays a crucial role in riskmanagement, fraud detection, customer behavior analytics, andautomation of financial processes. In this role, you will applymachine learning, advanced statistical techniques, and large-scaledata processing to develop models that enhance our BNPL platform.You will work closely with Engineering, Risk, and Product teams todeploy scalable, data-driven solutions that fuel business growth.Key Responsibilities: - Develop and deploy machine learning modelsto optimise credit risk assessment, fraud detection, andtransaction automation. - Analyse large datasets to extractmeaningful insights and drive data-informed decision-making. -Enhance our data pipelines and machine learning infrastructure,ensuring efficient model training and deployment. - Collaboratewith engineering, product, and risk teams to integrate data sciencesolutions into real-time production environments. - Conductstatistical analyses and A/B testing to validate hypotheses andimprove model performance. - Continuously research and experimentwith emerging techniques in machine learning, deep learning, anddata analytics. - 3-5 years of experience in data science, machinelearning, or a related field. - Strong programming skills in Pythonand SQL, with the ability to query databases and manipulate largedatasets. - Proficiency in key Python libraries for data science,including Pandas, Scikit-learn, Statsmodels, NumPy, SciPy,Matplotlib, TensorFlow, and Keras. - Solid understanding of machinelearning techniques, such as clustering, tree-based methods,boosting, text mining, and neural networks. - Expertise instatistical modeling and techniques such as regression, hypothesistesting, simulation, resampling methods, and stratification. -Degree in Data Science, Mathematics, Physics, Computer Science,Engineering, or another quantitative field (or equivalentexperience). - Strong business acumen with a problem-solvingmindset, ideally with experience in fintech or payments. -Excellent communication skills, with the ability to convey complextechnical concepts to both technical and non-technicalstakeholders. - Ability to work in a dynamic, fast-pacedenvironment, adapting to changing priorities and objectives. - 25days paid time off per year + public holidays - £500 annualallowance to spend on anything that will contribute to your mentalor physical health - £500 allowance towards a phone device every 24months (from your 6th month anniversary) - £500 annual allowancefor learning and training - Cycle to work scheme - Enjoy a flexiblework environment, balancing onsite and working from home#J-18808-Ljbffr
