Data Scientist / AI Engineer

NLP PEOPLE; London; Hybrid; GBP 50,000 - 90,000; Full time

Job summary

Join NLP PEOPLE as an Artificial Intelligence Engineer / Data Scientist in London. This exciting role offers the chance to work on diverse projects within a dynamic team, focusing on creating innovative data solutions. With a competitive salary and a strong emphasis on career growth, this position is ideal for professionals looking to advance in the AI field.

Qualifications

• Experience with AI techniques (ML, deep learning, NLP).
• Strong understanding of data manipulation and cloud deployment.
• Familiarity with software engineering and visualization tools.

Responsibilities

• Designing modern analytical data solutions.
• Engaging in the full life cycle of projects.
• Translating business requirements into technical solutions.

Skills

AI techniques

Python

R

Spark

SQL

Data Science platforms

Software engineering practices

Hadoop

Cloud technologies

Data manipulation/wrangling

Tools

Databricks

AzureML

Terraform

Job description

Artificial Intelligence Engineer / Data Scientist £50k – £90k dependant on experience bonus good bens. Flexible Working Location opportunity.

This role may suit individuals who have previously held roles such as Data Engineer, Data Architect, Big Data Consultant, Data Scientist, Data Modeller, Big Data Analyst, or AI Engineer.

We are assisting in recruiting AI Engineers / Data Scientists to join an innovative and growing team within the data practice of a prestigious global technology consulting firm. The client offers excellent career growth, professional development, and a personalized benefits package.

Candidates must ideally have UK security clearance and be fully flexible regarding working location. The successful candidate will be a key team member designing modern analytical data solutions, engaging in the full project lifecycle. The role offers a diverse range of exciting work.

Key Skills

We are recruiting at various levels within the salary range, so candidates are not expected to be experienced in all areas listed below.

• AI techniques (supervised and unsupervised machine learning, deep learning, graph data analytics, statistical analysis, time series, geospatial analysis, NLP, sentiment analysis, pattern detection, etc.)
• Python, R, or Spark for data insights
• Data Bricks / Data QISQL for data access and processing (PostgreSQL preferred, but general SQL knowledge is important)
• Latest Data Science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., TensorFlow, MXNet, scikit-learn)
• Software engineering practices (coding standards, unit testing, version control, code review)
• Hadoop distributions (Cloudera, Hortonworks), NoSQL databases (Neo4j, Elastic), streaming technologies (Spark Streaming)
• Data manipulation and wrangling techniques
• Development and deployment technologies (virtualisation, CI tools like Jenkins, configuration management with Ansible, containerisation with Docker, Kubernetes)
• Data visualization skills (JavaScript preferred)
• Experience deploying solutions on Cloud platforms (AWS, Azure, Google Cloud) including provisioning tools (Terraform)
• Strong interpersonal skills for client engagement and requirement gathering
• Ability to translate business needs into technical solutions
• Experience in designing Data Science projects, planning, and team leadership

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