National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

VP Product (Workplace)

Pod Point, Ltd.
London
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist - Media Optimisation

Data Science Analyst

VP Product (Workplace)

Department:Product

Employment Type:Full Time

Location:London

Reporting To:Chief Product & Technology Officer

Compensation:£110,000 - £130,000 / year


Description

Salary: Up to £130,000 per annum | + Eligibility for Pod Point Incentive Plan | Company EV | Hybrid - London

Leading the way in electric vehicle charging, we've been at the forefront of adoption in the UK since 2009. With over 250,000 charge points installed so far, out of a total of 1 million in the UK, we make EV ownership simple and affordable.

Partnering with top automotive brands like Mercedes, Jaguar Land Rover, BMW and Kia, as well as energy leaders such as EDF and Centrica, we’ve earned accolades such as the 'Which? - Trusted Trader' award and 'Best for Value, Home EV Chargers - What Car?'

With our international expansion, we aim to transform the EV charging landscape not just in the UK, but now across Europe.

Our Ways of Working

We’re all about flexibility, community and a healthy work-life balance. Our hybrid model offers a 'best of both worlds' approach combining the best parts of home and office working. When you'll be in the office depends on your role, but you can expect to work from our London office between 8-12 days per month.

To support this, the successful applicant should be within a reasonably commutable distance to our office (Gray's Inn Road, London, WC1X 8HB).

Join the EVolution:

The VP of Product - Workplace will lead and facilitate a value stream management team in an EV company. A cross-functional team bridging the gaps on the end-to-end delivery of propositions and offerings between commercial, marketing, operations and design. This role requires a deep understanding of the market, customer needs, business objectives, and technical feasibility. The ideal candidate will have a strong product lead and management background, coupled with expertise in value stream management, lean portfolio management, Kanban, flow optimization, and stakeholder management. This is a pivotal role that combines strategic vision with execution, driving innovation in the EV charging space.


Key Responsibilities:

  • Servant leadership and facilitation of a Value Stream Management team.
  • Running daily standups, regular operational and functional meetings.
  • Voice of product in the team.
  • Ensure creation of service blueprints and customer journeys to understand and improve our offering to the customer.
  • Work closely with product managers and their domains to manage requirements and estimations.
  • Implement frameworks to constantly measure customer success and company value, health and fitness.
  • Present quarterly to management and business on performance, roadmaps and commitments.
  • Utilise lean portfolio management and Kanban methodologies to prioritise and manage workflows effectively.
  • Prioritise strategic work mapped to company strategy to improve customer value and profitability.
  • Communicate strategic vision and high-level technical requirements to internal teams and external stakeholders.
  • Stay informed about industry trends, emerging technologies, and customer feedback to continuously evolve the offering.
  • Work closely with VP of Product – Home to ensure cross collaboration, synchronisation and alignment of work and tech.

Required Skills:

  • Proven experience as a Senior Product Leader in the EV industry.
  • End-to-end delivery of propositions, from ideate to operate.
  • Hands-on experience with agile practices.
  • Exceptional stakeholder management skills.
  • Analytical mindset with a focus on using data and metrics to inform decisions and measure success.
  • Excellent communication and organisational skills.

Bonus Skills:

  • Experience in the Energy industry.
  • Knowledge of agile frameworks and prioritisation frameworks like F4P.
  • Certifications in product management and/or agile methodologies.
  • Experience in service design/blueprints and value stream mapping.

Perks that spark joy:

  • Flexible hybrid working model.
  • Work abroad for up to 20 days per year.
  • Salary Sacrifice EV Scheme and free Pod Point.
  • Family & friend discount scheme.
  • 25 days holiday (plus Bank Holidays).
  • Very generous parental and family leave.
  • Pension scheme with a 4.5% matched contribution.
  • Eyecare scheme.
  • Life insurance covering up to 4x your annual salary.
  • Virtual GP provided by HealthHero.
  • Employee Assistance Program.
  • Free Mortgage Advice.
  • Discounted Gym Memberships.
  • Cycle2Work Scheme.

Important Information:

You must have the legal right to work in the UK. We celebrate diversity and encourage applications from all backgrounds. Your privacy is important to us, all information shared will be handled according to ourCandidate Privacy Notice.

#J-18808-Ljbffr

National AI Awards 2025

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Top 10 Mistakes Candidates Make When Applying for Machine-Learning Jobs—And How to Avoid Them

Landing a machine-learning job in the UK is competitive. Learn the 10 biggest mistakes applicants make—plus tested fixes, expert resources and live links that will help you secure your next ML role. Introduction From fintechs in London’s Square Mile to advanced-research hubs in Cambridge, demand for machine-learning talent is exploding. Job boards such as MachineLearningJobs.co.uk list new vacancies daily, and LinkedIn shows more than 10,000 open ML roles across the UK right now. Yet hiring managers still reject most CVs long before interview—often for avoidable errors. Below are the ten most common mistakes we see, each paired with a practical fix and a live resource link so you can dive deeper.

Top 10 Best UK Universities for Machine Learning Degrees (2025 Guide)

Explore ten UK universities that deliver world-class machine-learning degrees in 2025. Compare entry requirements, course content, research strength and industry links to find the programme that fits your goals. Machine learning (ML) has shifted from academic curiosity to the engine powering everything from personalised medicine to autonomous vehicles. UK universities have long been pioneers in the field, and their programmes now blend rigorous theory with hands-on practice on industrial-scale datasets. Below, we highlight ten institutions whose undergraduate or postgraduate pathways focus squarely on machine learning. League tables move each year, but these universities consistently excel in teaching, research and collaboration with industry.

How to Write a Winning Cover Letter for Machine Learning Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for machine learning jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the machine learning sector. When applying for a machine learning job, your cover letter is a vital part of your application. Machine learning is an exciting and rapidly evolving field, and your cover letter offers the chance to demonstrate your technical expertise, passion for AI, and your ability to apply machine learning techniques to solve real-world problems. Writing a cover letter for machine learning roles may feel intimidating, but by following a clear structure, you can showcase your strengths effectively. Whether you're just entering the field, transitioning from another role, or looking to advance your career in machine learning, this article will guide you through a proven four-paragraph structure. We’ll provide practical tips and sample lines to help you create a compelling cover letter that catches the attention of hiring managers in the machine learning job market.