Sanderson | Head of Product / Product Lead

Sanderson

London

1 year ago

Applications closed

Related Jobs

View all jobs

Senior SAS Data Engineer - SC Cleared

Data Engineer - DV Cleared

Head of Product / Product Lead / Senior Product Manager / AI Product Manager / Role purpose:This role will ensure we achieve a set of agreed outcomes across a substantial program of work, by creating and then delivering a roadmap with a continuous focus on quality, pace and the accurate measurement of impact. The role will focus will on optimising our business and service operations using cutting-edge predictive and prescriptive AI models, Data Science and Machine Learning to improve operational efficiency, reduce costs, and enhance customer satisfaction.The role:Define the product vision, goals, and roadmap, ensuring alignment with organisational objectives in line with the AI Strategy. Gather requirements from stakeholders, including operational teams and leadership, and translate them into actionable deliverables.Prioritise features and tasks based on business value, technical feasibility, and timelines.Collaborate with the team of Data Scientists and Engineers to develop innovative solutions for deployment optimisation.Partner with internal teams to ensure smooth integration of project into existing systems and business processes.Monitor project progress, manage risks, and address roadblocks to ensure timely delivery.Define success metrics and KPIs for AI initiatives and monitor their performance post-launch.Drive continuous improvement by incorporating feedback and analysing results.Communicate project updates, insights, and progress to stakeholders.Experience / Skills:Proven experience as a Product Manager / Leader in a technical or data-driven environment.Strong understanding of AI, Data Science, and Machine Learning applications.Exceptional communication, stakeholder management, and organisational skills. Able to convey ideas and technical content to different stakeholders, from engineers to senior executives.Experience with Agile methodologies and managing cross-functional teams.Experience of owning a complex data science/ Gen AI problem from ideas and discovery through to prioritisation, definition, delivery and post launch evaluation. Demonstrating sound decision making at each stageData Proficiency and Collaboration: Skilled in analysing raw data and using SQL and other data tools to visualise insights; effectively translates complex data needs into clear requirements for data science/Gen AI teams and actionable recommendations for stakeholders.Sufficient understanding of software development, data science and GenAI processes and design principles to be able to communicate and collaborate effectively with technical team; and to assess the implications of technical decisions on the product strategy and user experience.Track record of defining and delivering great analytical outcomes leading to commercial outcomes – and adept at balancing the two.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Feb 11, 2026

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Feb 3, 2026

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Jan 29, 2026

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.