Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Vice President of Product – Data and Insights

RedCloud
London
9 months ago
Applications closed

Related Jobs

View all jobs

Vice President of Artificial Intelligence

Risk Management – Data Scientist / Applied AI ML Lead - Vice President

Risk Management – Data Scientist / Applied AI ML Lead - Vice President

Data Scientist, Capital Team - Assistant Vice President

Data Scientist, Capital Team - Assistant Vice President

Data Scientist, Capital Team - Assistant Vice President - Citi

RedCloud is leveraging AI-powered technology to break down the barriers to fair and profitable trade in emerging markets. RedCloud's Intelligent Open Commerce Platform connects FMCG Brands, Distributors, and Local Merchants on a single, equitable marketplace, empowering them with real-world insights and data to help them make better decisions. RedCloud enables FMCG Brands to seize new opportunities in emerging markets, facilitates access to more buyers & streamlines operations for Distributors, and helps Local Merchants spend more time selling products, not searching for them.  The company comprises a highly diverse, dynamic team of driven talented people from over twenty different countries, speaking multiple languages, with a physical footprint in Africa, Europe, and Latin America.

We are seeking a visionary and strategic Vice President of Product for Data and Insights with deep expertise in data-driven products, particularly within the B2B commerce and FMCG (Fast-Moving Consumer Goods) industries. This role requires a robust understanding of data-as-a-service (DaaS) models, data monetization strategies, and a proven track record of converting complex datasets into actionable insights. Our ideal candidate will bring a balance of technical expertise and commercial acumen, with experience in designing and launching data-centric products that drive measurable business value.

As a VP of Product, you will own:

1. Data Product Strategy and Vision

  • Define the vision, strategy, and roadmap for data and insights products, focusing on monetisation, user engagement, and scalability.
  • Develop innovative data-as-a-service (DaaS) models and business strategies to enhance product value and revenue generation.
  • Leverage deep market knowledge, especially within B2B commerce and FMCG, to identify customer needs and create solutions that provide meaningful data insights for brands, distributors, and retailers.

2. Product Development and Lifecycle Management

  • Drive the end-to-end product lifecycle, from ideation and design to go-to-market strategies and execution, with a focus on experimentation and iterative improvement.
  • Collaborate with engineering, data science, and business teams to develop and implement cutting-edge machine learning and statistical learning algorithms, with applications in supervised and unsupervised learning.
  • Guide product teams in delivering impactful features such as price intelligence, demand forecasting, inventory optimization, and predictive analytics for brand and distributor decision-making.

3. Customer-Centric Data Insights

  • Transform complex datasets into actionable insights, enabling brands, distributors, and retailers to make data-driven decisions.
  • Focus on predictive and prescriptive insights that support initiatives such as bundling recommendations, cross-selling, and upselling for FMCG products.
  • Drive the development of recommendation engines and intelligent algorithms that improve customer engagement and product adoption, with an emphasis on accuracy, relevancy, and usability.

4. Business Model and Go-to-Market Expertise

  • Design and execute robust business models for data products, ensuring alignment with revenue goals, market demands, and customer needs.
  • Implement experimentation frameworks to validate product hypotheses and optimize product performance based on customer feedback and data analysis.
  • Lead go-to-market strategies for data and insights products, including positioning, pricing, and scaling across new and existing customer segments.

5. Cross-Functional Leadership and Collaboration

  • Build and manage cross-functional teams, fostering collaboration between data science, engineering, marketing, and sales to deliver cohesive and high-impact products.
  • Act as a thought leader within the company, educating teams on the power of data and insights while advocating for best practices in data governance and analytics.
  • Serve as a bridge between technical and commercial teams, ensuring that product decisions align with both technological advancements and business objectives.

Experience we like to see:

Experience: 10+ years in product management, with a strong background in data-driven product strategy and development. Proven experience within the B2B commerce and/or FMCG sectors is a significant plus. Technical Knowledge: Advanced understanding of machine learning, statistical learning, recommendation engines, and data-to-insights frameworks. Hands-on experience with supervised and unsupervised learning models, predictive analytics, and recommendation systems. Commercial Acumen: Strong grasp of data monetization strategies, business model design, and go-to-market strategies for data products, with a focus on customer-centric design and ROI. Analytical Skills: Proficient in data analysis, including experience with price intelligence, demand forecasting, inventory optimization, and similar data-to-insights conversions.

This role is ideal for a forward-thinking product leader with a passion for data and insights, an understanding of advanced analytics, and the ability to drive impactful change within a dynamic industry. If you're ready to elevate data products that empower brands, distributors, and retailers to make smarter, data-informed decisions, we’d love to hear from you.

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.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.