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Data Scientist


Overview

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Details

DESCRIPTION

CheckRecipient

CheckRecipient uses advanced machine learning and natural language processing (NLP) to make it impossible for sensitive information to end up in the wrong hands. We protect enterprise networks against new and intelligent cyber threats by preventing breaches in real-time.

Founded by a team of Imperial College engineers, we’re backed by some of the world’s leading technology investors. We work with international clients in the financial, legal and professional services sectors who trust us to find the most intelligent ways to keep their data secure.

Engineering at CheckRecipient

Dealing with massive datasets at scale requires ingenuity and strong analytical skills. Our agnostic approach to problem solving means we favour hiring engineers who pride themselves on the ability to learn new skills, their comfort with the unknown and their willingness to experiment.

At CheckRecipient you’ll be growing your skill-set on an ongoing basis; regular and continuous development is something we believe in and as an employee we will seek to create opportunities for you to evolve.

We build quickly and follow both agile and continuous delivery paradigms. As a member of the CheckRecipient engineering team, you will have the autonomy to work on your own projects, and be part of our regular round tables to bounce ideas around as a team on how to tackle our biggest challenges.

Here are some of the technologies we’re working with / interested in:

-Ruby, Python, Go

-Kubernetes, Rancher, Docker

-Kafka

-Postgres, DynamoDB, Cassandra

-Redshift, Spark, AWS, Microservices architecture

Awards

Winner - WIRED Security 2016 Best Startup Award

Winner - LegalGeek Best Machine Intelligence Start Up 2016

REQUIREMENTS

You should apply if you:

-want to join a fun and fast growing company

-are a great problem solver who takes pride in their work

-also believe that data scientists are most effective when they are responsible for getting ideas into production (see here)

- are happy getting your hands dirty data munging and working with unstructured data

-aren’t afraid by the unknown; there is little prior research for the problems we are tackling

-have strong SQL and python skills

-are comfortable working with big data technologies e.g. Redshift, Spark, or similar

-are happy to drive projects from idea to production without much guidance

-have a strong background in statistical analysis

Bonus:

-you have deployed machine learning into the wild, rather than for purely academic research

-you have experience working with NLP (extra special bonus: in document classification)

-interested in using deep learning with big datasets

BENEFITS

-Competitive salary and meaningful equity options

-Choose your own kit

-Central London office location

-Regular team socials and activities

Important Notices:

-We do not accept applications or résumés from 3rd party recruiters.

-We are currently unable to sponsor applicants who do not have a right to work in the UK

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