Posted 16 Mar

Data Scientist

London, United Kingdom Full Time

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 £2 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.

The role

Data Science at Zopa is hands-on and quantitative. Our Data Scientists propose ideas, formulate them as hypotheses, test them with statistics, and present insights with actionable information across a broad range of topics, such as risk, marketing, fraud, pricing, and operations. Working within a multi-disciplinary team using the latest technologies in analytics and big data, a Data Scientist at Zopa will have the programming skills to go beyond what the tools can do.

About you

You are detail oriented and obsessed with data quality. You are strong in transforming and modeling data at scale, machine learning, and statistics. You have good business acumen and are interested in how companies operate and create revenue. You have an inquisitive mind, are intrinsically curious and are passionate about deriving insights from data.

Essential skills/knowledge:

  • A degree (MSc or Ph.D.) or equivalent in Computer Science, Physical Sciences, Applied Math, or similar
  • 2+ years of experience in data science, business intelligence, analytics, or academic research
  • Strong programming ability in Python
  • Experience using the PyData stack for analytics/machine learning, and especially scikit-Learn, pandas, Numpy, MatPlotLib, SciPy
  • SQL
  • Linux/Unix

Bonus points for:

  • Degree (MSc or PhD ) in Machine Learning or Applied Statistics
  • Strong knowledge of statistics (e.g., Bayesian inference, Bootstrap, hypothesis testing, confidence intervals, maximum likelihood, Monte Carlo).
  • Experience with mathematical optimization (esp. linear programming)
  • Experience adding value from data in a business setting.
  • Success in data science competitions, such as Kaggle and KDD Cup.
  • Experience at profiling and increasing the speed of your Python code (e.g., with Cython, Numba, PyPy).
  • Experience using Hadoop (HDFS, Hive, HBase, Spark, MLLib)
  • Knowledge of deep-learning fundamentals, and preferably real-world experience at developing deep-learning models (e.g., with Theano, TensorFlow, or Keras).

“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."

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