Data Scientist

Morgan Spencer
Charing Cross, United Kingdom
9 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Junior

Job location

Charing Cross, United Kingdom

Tech stack

Artificial Intelligence
Data analysis
Information Engineering
Machine Learning

Job description

As a Data Scientist you will be working collaboratively within a project team to help rail industry clients. Your work location will be a mix of central London office, client sites and home office.

This role provides the platform to take your career to the next level. You will be working alongside experienced rail consulting and product design colleagues. As a start-up there is also plenty of space for you to lead an area of business development (such as marketing, recruitment, learning & development).

Day-to-Day Work

Day to day work will be a mix of data science / AI / machine learning / data analysis / data engineering and cloud based tasks.

Requirements

This post is for you if: you are an experienced Data Scientist / Data Consultant (min. 1-2 years' experience using rail data) OR Data Scientist with experience in other industry (min. 2-5 years) and looking to make a career transition to rail consulting. There is naturally a particular interest in speaking to candidates with data science experience in rail, since this is the specialism of the business.

In addition to the above you should have solid AI / Machine Learning / Data Science theory and be a team player, collaborative and pro-active in your approach to problem solving.

About the company

This fast-growing start-up is like an app store for the railway, taking complex rail data and creating bespoke products/apps for rail staff to use day-to-day. It also provides consulting and data science expertise to help the rail industry tackle its most difficult problems. Every day brings new challenges and as a Data Scientist there is an opportunity to make a visible difference from Day 1.

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