Product Owner - VisNET

Capenhurst
8 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Analyst

Senior Data Engineer

SAS Data Engineer

Machine Learning Engineer

Senior Data Engineer (Fabric)

EA Technology is a well-established, positive culture-based company with innovation and creativity at our core. We are a forward thinking business and we live by our values: Collaboration, Creativity, Integrity and Impact. This ensures employee wellbeing is always at the forefront and our amazing people have the autonomy to do their best work.

We encourage and cultivate individual creativeness, understanding that every person at EA Technology is critical to achieving our company goals. This spirit impacts our internal culture and the positive way we interact which is why so many of our employees stay with us long term.

Due to significant growth and expansion, we have a vacancy for a Product Owner to join our VisNet NIFT (Network Investment Forecasting Tool) team so, if you’re a technically savvy Product Owner/Manager who is passionate about optimising networking planning, investment forecasting and data driven decision making, we’d love to hear from you!

this role is remote with fortnightly visits to our Capenhurst site (CH1 6ES)

About the role:
As a Product Owner for VisNet NIFT, you will be responsible for driving the development, execution and enhancement of the Network Investment Forecasting Tool (NIFT).
• Collaborate with engineering, data science, operations and external stakeholders
• Ensure that NIFT provides accurate, actionable and scalable solutions for network constraint analysis, solution deployment and financial forecasting
• Co-ordinate across teams and ensure NIFT aligns with strategic goals and industry standards
• Ensure alignment with business and regulatory objectives
• Work closely with engineering, data teams and UX specialists to refine and enhance NIFT’s capabilities
• Define and oversee constraint analysis, financial modelling and solution deployment workflows
• Ensure seamless data integration, forecasting accuracy and usability improvements in NIFT
• Drive cross functional collaboration to improve map visualisations, asset-specific insights and reporting tools
• Establish and track KPIs to measure NIFT’s effectiveness including forecast accuracy, model performance and adoption rates
• Champion continuous improvement

What we’ll need from you:
• Proven experience in Product Management; particularly in energy, utilities or grid forecasting technologies
• Strong understanding of network modelling, data analytics and constraint forecasting methodologies
• Experience working with geospatial visualisation tools, RAG status indicators and map-based dashboards
• Ability to manage complex data integrations and system interoperability challenges
• Ability to translate technical requirements into actionable product features
• Familiarity with regulatory frameworks, DFES data and utility network investment strategies
• Experience in network constraint analysis, financial modelling and scenario forecasting
• Background in network infrastructure, system engineering or data science
• Experience working with DNOs and large-scale infrastructure forecasting projects
• Strong understanding of user experience principles for technical applications

What we can offer you:
At EA Technology, we believe in growing with our people. In addition to a great working environment, we offer you:
• Up to £70,000 + annual bonus based on business & individual performance
• Career development opportunities: We offer genuine pathways for growth within our company.
• Work-life balance: With flexible working options, we support our employees in balancing their professional and personal lives.
• Holidays: 25 days of annual leave, plus bank holidays, with an extra day for every three years completed (up to a maximum of 30 days). Ability to buy an additional 5 days.
• Pension contributions of 8% from the employer (or cash equivalent).
• Comprehensive benefits, including Group Life Insurance, Income Protection, and Critical Illness cover (or cash equivalents).
• Private Medical Insurance (single cover or cash equivalent).
• A truly collaborative and supportive work environment where amazing colleagues inspire each other every day

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

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

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

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.

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.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.