Lead Data Scientist - London or Gloucester - Hybrid - £75k

Job Description

Lead Data Scientist - London or Gloucester - Hybrid - £75k

This is an excellent opportunity for an experienced data scientist to step into a lead role in a dynamic organisation that is agile and responsive. A business that is growing fast and where you get to drive and shape the future. You will bring experience in data science, machine learning algorithms, data analytics, and data engineering. You will also be highly capable with relevant tech stacks such as Python, AWS, Azure, CI/CD etc. You must also either hold active SC clearance or be eligible for SC clearance to be considered for this role.

Salary & Benefits

• £75,000 salary
• Hybrid working: 2-3 days in London or Gloucester office
• 25 days annual leave with option to buy or sell extra days
• 10% performance related bonus
• Company contributory pension scheme
• Private healthcare

Role & Responsibilities

• Leading client projects and providing subject matter expertise.
• Working in scrum-like environments for iterative and 'fail-fast' work and innovation.
• Working in cross-disciplinary teams.
• Working at the PoC (proof-of-concept) stage through to MVP and MMP stages.
• Assessing your clients' business and technical needs with the ability to identify opportunities for data science to be used. Managing client and stakeholder relationships appropriately.
• Solving problems using data science techniques and in a scientifically robust fashion.
• Identifying data sources that are relevant to client needs, and related data science concepts that leverage those sources to aid the client.
• Working with various forms of data (e.g., unstructured, semi-structured or structured; text, time-series or image) and suitably modelling them (e.g., table, key-value pair, graph) for efficient data science use.
• Applying statistical and evidence-based techniques to inform insights and actions from the data.
• Communicating technical content at the right pitch/level both internally and to customers.
• Presenting to the client, using data science tooling and investigation, a 'story' of the data.
• Building maintainable code that uses existing data science libraries, implements existing data science techniques, or implements novel techniques.
• Designing, evaluating, and implementing on-premise, cloud-based and hybrid data science and machine learning techniques and algorithms (including providing relevant review and guidance on testing aspects, identification of risks and proposing and implementing their mitigations).
• Developing scalable models and algorithms that can be deployed into production environments.
• Supporting client engagements, including pitches and presentations.

What do I need to apply

• You have experience of working in a consultancy, engineering, or data industry.
• You have led client delivery across a range of projects, e.g., data science, data analytics, data engineering, data intelligence, data security and proven experience in relevant technologies (e.g., Python applied to data science), as an individual contributor and leading a small team.
• You have experience working on cloud-based infrastructure (e.g., AWS, Azure, GCP).
• You have demonstrable continuous personal development.
• You have strong interpersonal skills.
• You have experience with using CI/CD tooling to analyse, build, test and deploy your code and proven experience in their technologies.
• You have experience in database technologies (e.g., SQL, NoSQL such as Elasticsearch and Graph databases).
• You have a good understanding of coding best practices and design patterns and experience with code and data versioning, dependency management, code quality and optimisation, error handling, logging, monitoring, validation and alerting.