Data Scientist / AI Engineer
NLP PEOPLE · London, United Kingdom ·
- Category
- Data science
- Salary
- GBP 50,000 – 90,000 / year
NLP PEOPLE · London, United Kingdom ·
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An AI Engineer / Data Scientist joins the data practice of a global technology consulting firm in London, designing modern analytical data solutions across the full project life cycle. Day-to-day spans machine learning, deep learning, NLP and data engineering using Python/R/Spark, SQL, Databricks and cloud platforms, at £50k–£90k plus bonus.
Artificial Intelligence Engineer / Data Scientist £50k – £90k dependant on experience bonus good bens. Flexible Working Location opportunityThis 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 EngineerWe have been asked to assist in the recruitment of AI Engineer / Data Scientists to join an innovative and growing team within the data practice of this prestigious global technology consulting firm. Our client offers excellence in career growth, professional development and a coveted personalised benefits package.
Candidates must ideally 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 diverse role, with an exciting variety of work.Key Skills
Again, we are recruiting at various levels (in the above salary brackets) so we are not expecting candidates to be experienced in all of the areas outlined below.
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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 dataData Bricks / Data QISQL 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 techniquesExperience 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) including Cloud provisioning tools (e.g. Terraform)Strong interpersonal skills with the ability to work with clients to establish requirements in non-technical language.Ability to translate business requirements into plausible technical solutions for articulation to other development staff.Experience designing Data Science deliveries, planning projects and/or leading teams
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