Head of Data Science

About RedCloud

The global supply chain is broken—creating a $2 trillion inventory gap where essential consumer goods fail to reach the people who need them. Brands miss sales, distributors mismanage stock, and retailers face empty shelves. The result? Higher prices, slower growth, and lost opportunity across the board. RedCloud is fixing this. Our RedAI digital trading platform, bulk and retail trading exchanges connect key parts of the supply chain—enabling bulk inventory exchange, streamlined digital payments, and generating vast quantities of aggregated market data. By applying AI and machine learning techniques, we deliver predictive market insight and trading recommendations straight back to the trading environment—facilitating smarter everyday business decisions for our customers, from factory to warehouse to store. Headquartered in London, RedCloud became a publicly listed company on Nasdaq (RCT) in March 2025. With a diverse team spanning many nationalities and operations across Africa, the Middle East, Europe, and Latin America, we’re building a more connected and efficient global trade network. Our AI labs are busy exploring the next generation of smart AI agents and deeper FMCG market intelligence for the benefit of our customers across a growing operational footprint.

The Role

The ideal candidate will bring strong leadership experience in data science, strategic vision for data-driven initiatives, and a proven track record of delivering business impact. Key requirements are a deep technical understanding of data science, machine learning, and MLOps, alongside the ability to build and lead teams, communicate complex ideas to stakeholders, and align data strategy with broader business goals. You will play an integral role, taking ownership of a team focused on designing, developing, and deploying ML systems to solve real‑world problems and enhance business processes, leveraging cloud platforms to build, train, and scale ML models. As Head of Data Science, you will lead the development and implementation of state‑of‑the‑art algorithms, including Computer Vision techniques, LLMs and other GenAI models. Collaborating closely with multiple stakeholders and cross‑functional teams, including Data and Software engineers, to integrate AI solutions into existing systems. Working with Product and business stakeholders to understand challenges and translate them into efficient AI‑driven products aligned with broader business goals. Keeping up with the latest advancements in AI, researching new techniques and implementing them to enhance the performance and accuracy of solutions.

What You’ll Do

• Strategic leadership: Develop and implement data science and AI strategies, aligning them with company‑wide objectives.
• Team leadership: Build, manage, and inspire a high‑performing data science team through setting objectives, performance management, and talent development.
• Technical direction: Define the technical roadmap, champion best practices, and drive the transition to production‑level machine learning engineering.
• Stakeholder management: Collaborate with senior leaders and other stakeholders to identify new opportunities and ensure data science solutions meet business needs.
• Innovation and delivery: Oversee the design, development, and deployment of data science solutions, from research to production, and maintain a focus on innovation.
• Communication: Translate complex data science concepts into clear, compelling, and user‑friendly information for various audiences, including senior leadership.
• Governance and ethics: Ensure data governance and ethics are embedded in organizational strategy and champion these principles across the company.

What You’ll Need

• Leadership and management: Significant experience as a senior leader in a data science or AI‑related role, with a track record of managing multi‑disciplinary teams and budgets.
• Technical expertise: Deep technical knowledge of the entire data science lifecycle, including data engineering, machine learning, and MLOps.
• Programming and analytics: Proficiency in programming languages such as Python, R, or SQL, and experience with various data science and machine learning libraries.
• Experience with libraries/frameworks like NumPy, Pandas, SciPy, Scikit‑learn, TensorFlow, PyTorch, Transformers, Langchain, Streamlit, or Gradio, among others.
• Experience with cloud‑based tools for production use (e.g., AWS SageMaker, AWS Bedrock, Vertex AI, Azure Machine Learning, Azure OpenAI).
• Knowledge of databases and data technologies, such as Snowflake, BigQuery, and relational databases like SQL.
• Business acumen: Strong understanding of how to apply data science techniques to solve business problems and deliver tangible value.
• Communication and influence: Excellent communication skills with the ability to build trust, influence stakeholders, and advocate for data‑driven decisions.
• Project management: Proven ability to scope, design, implement, and evaluate data science projects to tight deadlines.

Benefits

Working with a pioneering provider of eCommerce solutions you will have the opportunity to join an international company who are growing massively, we encourage ambition and creativity. Plus, You Will Get 25 Days Annual leave, increasing to 26 days after 12 months in the business Enhanced Company Pension (Matched up to 5%