Data Science Manager

SVGC limited; Milton Keynes; Hybrid; GBP 65,000 - 75,000; Full time

Job summary

Hostingersite is seeking a Data Science Manager in Milton Keynes for a hybrid role with on-site and client engagement. You will lead a team of Data Scientists, deploy AI solutions across multiple projects, and interact with customers and internal teams to turn ideas into scalable outcomes.

You should have a numerate degree, strong analytical skills, and experience with GenAI, ML, MLOps, and cloud platforms (Azure/AWS). Security clearance eligibility is required.

Qualifications

• A degree in a numerate subject such as Mathematics, Engineering or Physics or equivalent vocational experience.
• Strong analytical and statistical skills.
• Experience in public sector or private sector business processes where AI, and particularly GenAI, have been developed and deployed to achieve tangible benefits.
• Excellent ability in using tools such as MS Office and visualisation/analytical environments such as Power BI.
• Experience in leading, managing, developing, mentoring a team of Data Scientists working on multiple activities covering research, experimentation, proof of concept, development and delivery/support.

Responsibilities

• Lead and manage the end-to-end lifecycle for development and deployment of advanced AI, including MLOps and GenAI/LLMOps.
• Define technical standards, best practices and coding standards for AI and contribute to ATRS submissions to the UK Government.
• Support workshops, discovery activities and requirements gathering for client projects.
• Be the primary point of contact for data science issues across multiple projects.
• Ensure quality assurance of all data science activities and maintain documentation.

Skills

Team leadership

Data science

AI/GenAI

ML/Ops

Stakeholder engagement

Cloud platforms

Communication

Strategy & planning

Risk management

Education

Numerate degree

Tools

Power BI

MS Office

Azure

AWS

Job description

Grade/Salary: £65,000 to £75,000 depending upon experience
Location: Hybrid Home and on-site Milton Keynes. Typically, 1-2 days a week on-site
Contract type: Permanent
Travel: To client sites mainly Milton Keynes
Hours: 37 hours per week
Reporting to: Anthony Hornidge

The Role

Owing to our continued growth and trusted reputation, we are seeking a skilled Data Science Manager to join our team. This is an exciting opportunity to join an organisation with multiple lines of business (many of which will demand the deployment of a range of AI solutions) and lead and manage a team of Data Scientists to research, develop, deploy and provide support for AI solutions in significant public sector procurement.

The ability to communicate effectively and engage with customers and the wider team is critical.
You will be the primary point of contact for all data science issues across multiple concurrent projects.
This role is for someone who wants to inspire in return we offer the freedom to turn your ideas into reality. To support this the company operates an Innovation Board programme where proposals, which may not necessarily be associated with current contracts, can be submitted for consideration and company funding.

Responsibilities

Your main responsibilities will be to…

• Have an in-depth knowledge of the management, methods for development, methods for deployment, ML-Operations and procurement of AI solutions in multiple projects and/or solution elements, and specifically:
  Understanding and Management of Generative AI and associated technologies and methods
  Understanding and Management of Machine Learning and associated technologies and methods
  Understanding and Management of General AI techniques, data analytics (e.g. predictive), NLP etc.
• Lead (direction) and manage the end-to-end lifecycle for development and deployment of advanced AI, and specifically:
  The management of people, process, documentation associated with the development, deployment, maintenance, training and operational management of Machine Learning solutions (MLOps)
  The management of people, process, documentation, maintenance and operational management of Generative AI solutions (GenAIOps /LLMOps)
• Manage, objectively assess and track Technology Readiness Levels (or the equivalent) knowing how to progress from the Research into Development to integration and operational deployment.
• Contribute hands‑on input to design, development, testing, analysis, assurance, integration, deployment and support.
• Overall quality assurance of all data science activities including working with academic communities and supplier organisations.
• Support the business decision making through objective recommendations on the selection of appropriate AI approaches and technologies for a range of technical and operational challenges.
• Assess and optimise the scalability, security and maintainability of technical solutions.
• Think strategically and commercially with the ability to align technical solutions to business outcomes.
• Contribute (from time‑to‑time) to other operational support activities as required, including the resolution and/or management of operational support tickets. These may or may not include AI-based elements.
• Define and deliver where required, technical standards, best practices and coding standards for AI, including the requirement for ethical AI and take the lead for the development of Algorithmic Transparency Recording Standard (ATRS) submissions to the UK Government.
• Conduct technical reviews and assure the quality of AI models and software developed by the data science team and 3rd party contractors.
• Identify opportunities to help clients solve problems using appropriate Data Science techniques. This will include providing guidance and assistance where required to other lines of business so that corporate AI capability is advanced.
• Support workshops, discovery activities and requirements gathering.
• Be adept with both Predictive Analytics environments as well as ML Classifiers.
• Develop solutions for, and in deploying on, public and private cloud technologies, particularly Azure or AWS.
• Manipulate, process, and extract value from large, disconnected datasets using appropriate tools,
• Conceive, establish, manage, and maintain client‑centred relationships with the Data Science team, colleagues and clients.
• Build a network of contacts and share knowledge for mutual benefit.
• Currently hold Security Checked (SC) or be eligible and willing to achieve SC clearance.
  Note that eligibility requires sole British nationality or Dual nationality, one of which must be British together with 6 years consecutive residency in the UK.
• A degree in a numerate subject such as Mathematics, Engineering or Physics or equivalent vocational experience.
• Have strong analytical and statistical skills
• Experience in public sector or private sector business processes where AI, and particularly GenAI, have been developed and deployed to achieve tangible benefits.
• Excellent ability in using tools such as MS Office and visualisation/analytical environments such as Power BI.
• Excellent verbal and written communication skills, with the ability to clearly present complex information to technical and non-technical stakeholders.
• Experience in leading, managing, developing, mentoring a team of Data Scientists working on multiple activities covering research, experimentation, proof of concept, development and delivery/support.
• Experience in the identification of individual capabilities, work allocation, management and monitoring of work across projects and workstreams.
• Strong configuration control approach and proactive approach to documentation.
• Ability to take managed risks and assess their impact effectively.
• Experience in following financial procedures to monitor contract progress, ensuring deliverables are achieved OR milestones are achieved.
• Ability to manage suppliers/stakeholders contributing project components of a larger Data Science oriented programme of work.
• Knowledge in key Machine Learning based algorithms: Supervised (Linear regression, SVM, Random Forests, Gradient Boosting and Neural Networks) and Unsupervised (KMeans, Gaussian Mixtures) and the entire end to end ML pipeline.
• Experience of managing NLP problems such as Text Classification, PII detection, Sentiment Analysis, Text Summarization, Information Retrieval etc.
• Experience of managing NLP techniques such as N-grams, word embeddings and/or transformer-based systems.
• Experience of managing NLP techniques such as N-grams, word embeddings and/or transformer-based systems.
• Software integration and management of CI/CD environments