Data Excellence – Data Science
At Zopa, we’re shaping the future of finance.
We offer simple loans and smart investments that help people take control of their finances and do more with their money. In the 12 years we’ve been in business, we’ve helped more than 60,000 people lend over £3 billion to 246,000 UK consumers.
And our journey’s only just beginning. In November 2016 we announced our plans to build a next generation bank so that we can bring a greater range of smart, ethical finance products to even more people.
Data scientists at Zopa work on a broad range of topics such as risk modelling, pricing, marketing and operational research. The daily job of a data scientist includes extracting actionable insights from data with statistical analysis, identifying problems and opportunities in the business, proposing new ideas and experiments, developing and deploying machine-learning models and optimization algorithms in production.
Data scientists at Zopa work primarily as part of cross-functional teams known as Tribes, which are autonomous groups with ownership of one of our products, such as personal loans, P2P investments, credit cards, etc. Data scientists interact daily with analysts, product managers and software engineers in their own Tribes.
Data scientists also have close interactions with each other through the functional group known as the Data Excellence Chapter, where we share knowledge and experience on data science technologies and research. You may also help build our AWS analytical infrastructure with data engineers, mentor data analysts, and contribute to our efforts on Data Democratization.
You love data. You are passionate about solving real world problems with data. You have solid knowledge and hands-on skills in data processing, machine learning and statistical analysis.
You are a scientist. Always curious and eager to learn. You have an inquisitive mind to delve under the surface and challenge status quo. You are fearless in innovation, for the good of our customers and the world.
You are a great communicator. You do not shy away from engaging people of different background and you can communicate data science ideas effectively and convincingly.
You are a team player, striving for the success of the team with strong commitment to get the job done.
- Excellent programming skill in Python
- In-depth knowledge and hands-on experience of the PyData stack (e.g. Pandas, Numpy, Scipy, MatPlotLib, Scikit-learn) for analytics/machine learning
- Solid knowledge of statistics (e.g., Monte Carlo, hypothesis testing, confidence intervals, maximum likelihood, bootstrap, Bayesian inference)
- In-depth knowledge and hands-on experience in machine learning algorithms: linear regression, random forest, gradient boosted trees, neural networks, k-means, etc
- Proficiency in SQL
Bonus points for:
- A STEM degree, preferably PhD
- 4+ years of experience in analytics or scientific researches
- Experience of full life-cycle of a data science project, from data collection, EDA, model building to deployment
- Experience in optimization algorithms, deep learning, reinforcement learning
- Experience with AWS services (S3, RedShift, Athena, Glue, SageMaker, etc)
- Domain knowledge in credit risk, data-driven marketing, operational optimization
- Good understanding of best practice in software engineering
- Proficiency in Linux/Unix
- Success in data science competitions
- Contribution to open source projects
We are committed to equality of opportunity for all staff and applications from individuals are encouraged regardless of age, disability, sex, gender, sexual orientation, pregnancy and maternity, race, religion or belief and marriage and civil partnerships.