Data Scientist - Junior/Mid level

We have a data-driven culture. We recognise that in this digital era, data wealth and the ability to leverage it effectively is what will set us apart. As such, we are looking for a high-caliber data scientist to join our wonderful team of talented and experienced data scientists. Ideal candidate should have a passion for building highly scalable and optimised decision engines, as well as providing insights that can drive strong business value.

The role would involve building and deploying Two’s best-in-class decision processes to accurately measure credit risk as well as delivering a great service to our partners. Whatever background you come to us from, you will quickly find you are a world expert in credit management in the B2B e-commerce space.

Technologies We Use

• Python for data exploration, analysis, model design, and deployment

• BigQuery, Postgres, Hadoop, and Spark for distributed data storage and parallel computing

• Hosted on Google Cloud Platform

Your day-to-day will involve

• Carrying out exploratory data analysis on internal and external data sources with the purpose of deriving predictive insights or supporting data-driven decision-making.

• Designing and deploying Machine Learning models onto our decision engine to establish and enhance robust risk management controls, in line with business risk appetite.

• Engaging in feature engineering to identify predictive and effective model inputs.

• Working with data engineers to implement and improve data collection techniques to enhance the data wealth of the business for insights and model design.

• Developing processes and tools to monitor decision processes outcomes to identify areas of optimisation.

• 1-3 years of experience manipulating data sets and building statistical and machine learning models

• University degree in fields such as Data Science, Mathematics, Physics, Computer Science, Software Engineering or any other quantitative field or strong relevant experience.

• Proficiency in using Python and SQL to query databases, manipulate data and draw insights from large data sets.

• Strong familiarity with key Python packages for Data Science such as Pandas, SciKit-Learn, Statsmodels, NumPy, SciPy, Matplotlib, TensorFlow, Keras, etc.

• Good knowledge of key machine learning techniques such as clustering, tree methods, boosting, text mining, artificial neural networks, etc.

• Good knowledge of advanced statistical techniques and concepts such as regression techniques, simulation, resampling methods, stratification and sample selection, hypothesis testing, etc.

• Self-starters with strong business acumen, an entrepreneurial mindset, and problem-solving skills with an emphasis on product development.

• Excellent written and verbal communication skills for communicating effectively in teams of technical and non-technical individuals.

• Adept to working in a rapidly changing environment with dynamic objectives and iteration with users.

• 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