Python Data Scientist, up to £80k – Machine Learning

Central London, UK

up to £80k

Experienced Python Data Scientist with a broad and deep knowledge of machine learning techniques and practices? Want autonomy, constant learning and recognition?

Join one of the most sophisticated teams of PhD-level data scientists in insurance. 

There’s no room for guessing within insurance, so you’ll help build risk models that fundamentally change the insurers’ viewpoint, shifting them from an assumption-based understanding of risk, to an empirical, data-driven view. This role is essential to company success.

The business is developing a machine learning driven product, and as a Python Data Scientist, you’ll work on some of the company’s most integral and toughest challenges. You’ll apply advanced machine learning algorithms to insurance risk models, developing natural language processing algorithms to generate terabytes of training data from diverse structured and unstructured data sources.  As Data Scientist, you’ll model complex and varied insurance risks using both traditional generalised linear models and recent predictive risk modelling methodologies based on neural networks.

To succeed you will:

  • Bring your experience: To make the biggest impact you will have a broad and deep knowledge of machine learning techniques and practices that are clearly evident in the projects you’ve already worked on. You have minimum two years experience in Data Science as well as technical experience with some of the core Python data science libraries (scikit-learn, Numpy/Scipy, pandas, matplotlib, Jupyter notebooks). You’ve also got data manipulation and data visualisation skills. If you’ve had exposure to production level engineering (including concepts like test-driven development and continuous integration) we’ll be impressed, but it’s not essential. We use Apache Spark for processing of multi-terabyte datasets, so familiarity with distributed computing and analysis concepts would be useful.
  • Present with confidence: Your customers will include some of the largest insurance companies, and you’ll be expected to present your modelling results to their actuarial and underwriting teams, both via in-person presentations as part of our business development and by contributing to sales and marketing collateral. So you know what you’re talking about.
  • Get geeky: You’re passionate about data science and keeping up with current research, and probably have an advanced degree to underpin this. The conference budget encourages you to network with peers and present your work at industry and academic conferences, staying at the bleeding edge of developments.
  • Learn fast: You pick up new technologies and concepts quickly, applying them to real-world situations. You’ll develop hands-on experience with the plethora of technologies that enable data-driven risk models, gaining exposure to the multitude of insurance sectors that are being transformed by the outputs of these predictive models.
  • Keep learning: You’ll join some of the brightest minds in machine learning and risk modelling to solve real-world problems, helping insurers generate fairer premiums and enabling society at large to transfer risk in new and seamless ways.
  • Thrive on autonomy: Your originality and independent thinking will be celebrated, and you’ll work in decentralised teams, giving you the authority to own and solve problems creatively.

This is not just Data Science. This is about enabling a more secure society. 

Click here to APPLY NOW! Data Science


Write “I’m the experienced Python Data Scientist you need!” in your covering email (I want to know you read the whole advert and that you’re up for the challenge!).   

Dig out that passport – you’ve gotta be able to work in the UK.


More about the company

The salary is competitive but there’s more, like share options, augmented by private health insurance. The office is in Central London and with more snacks than you can imagine, a bar on site and surrounded by vibrant, fascinating colleagues, you’ll feel right at home.

We believe that in the next decade, insurance will develop the data liquidity associated with asset management and sports betting. We need your bright mind and voracious appetite for learning to help build this future. The goal is that in 10 years time, insurance will resemble asset management (real-time portfolio optimisation) and betting (closed systems with dynamic probabilities).

You’ll join a team building a new way to conceptualise, price and deliver insurance underpinned by liquid access to data in a technology-enabled economy. The Risk Engine simultaneously improves the accuracy and sophistication of risk selection and removes friction associated with the insurance buying process by replacing questions with thousands of data inputs. It extracts and fuses together billions of online data points relevant to commercial risk, helping insurers to differentiate risks at a higher level of granularity and discover new segments in areas where they have zero underwriting experience and claims history.

Your working days will begin with a stand up to synchronise efforts across the team, informed by weekly sprint planning with the whole company. In fortnightly one on ones with our Head of Data Science, you’ll gain in-depth feedback on performance and map out areas for targeted near-term personal development.

Test-driven development is a matter of pride, and the team peer review colleagues’ pull requests to ensure everything built is simple, elegant, reliable and self-documenting. You’ll be challenged and pushed to achieve more than you thought was possible, simultaneously helping those around you to reach their potential.

And what about the tech?

Python is used for most application development and data science, consuming all major numeric libraries including Numpy/Scipy/pandas, scikit-learn and TensorFlow/Keras. For NLP we incorporate CoreNLP and spaCy, and data persistence layers are built on top of ElasticSearch and PostgreSQL, with processing and analytics in Apache Spark, BigQuery and Kubernetes, deployed across the Google Cloud Platform and AWS.

Can you afford to miss this Data Science opportunity…?

Click to APPLY NOW.

  • Permanent
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  • Category: Technology
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  • Job Ref: 251117
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  • Date Posted: 26/11/2017
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