Senior Data Scientist / AI Engineer


Job Reference
Senior Data Scientist / AI Engineer
Job Type
Flexible - Nationwide offices
Salary Details
Salary range £60k - £140k, dependent on experience
Start Date
Key Skills
Artificial Intelligence, Data Science, Data Engineer, Big Data, Machine Learning, Deep Learning, Python/R/Spark, Hadoop, Cloud, SQL
Peter Hirst
07917 725773

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Job description

Artificial Intelligence Engineer / Data Scientist / Data Engineer

10+ roles at various level’s, ranging from £35k - £90k dependant on experience + bonus + good bens. Flexible Working Location

This role may suit individuals who have perhaps previously held the following role titles: Data Engineer, Data Architect, Big Data Consultant, Data Scientist, Data Modeller, Big Data Analyst, AI Engineer

We have been asked to assist in the recruitment of a Bid Data Engineer to join an innovative and growing team within the data practice of this prestigious global technology consulting firm. Our client offers good career path, professional development and a coveted personalised benefits package. Candidates must have UK security clearance, and be fully flexible on working location.

The successful engineer will be a key member within a team designing the modern analytical data solutions, engaging in the full life cycle of projects. This will be a hands-on and diverse role, with an exciting variety of work.
Key Skills – Again, we are recruiting at various level’s so not expecting candidates to be experienced in all of the areas outlined below.
• AI techniques (e.g. supervised and un-supervised machine learning techniques, deep learning, graph data analytics, statistical analysis, time series, geospatial, NLP, sentiment analysis, pattern detection, etc.)
• Python, R or Spark to extract insights from data
• SQL for accessing and processing data (PostgreSQL preferred but general SQL knowledge more important)
• latest Data Science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g. Tensorflow, MXNet, scikit-learn)
• Software engineering practices (coding practices to DS, unit testing, version control, code review)
• Hadoop (especially the Cloudera and Hortonworks distributions), other NoSQL (especially Neo4j and Elastic), and streaming technologies (especially Spark Streaming)
• Deep understanding of data manipulation/wrangling techniques
• Experience using development and deployment technologies, for instance virtualisation and management (e.g. Vagrant, Virtualbox), continuous integration tools (e.g. Jenkins, Concourse, Drone, Bamboo), configuration management tooling (e.g. Ansible) and containerisation technologies (e.g. Docker, Kubernetes, Swarm)
• Delivering insights using visualisation tools or libraries (Javascript preferred)
• Experience building and deploying solutions to Cloud (AWS, Azure, Google Cloud)