Deployment Strategy Principal

We do this as an "active co-sponsor", co-underwriting deals with top-tier Private Equity firms and deploying our own in-house team of data scientists, engineers, and strategists to execute value creation projects at the companies we invest in. Investing across North America and Europe, we currently have four portfolio companies. 

The Role

Deployment Strategy Principals are commercially focused leaders who have expertise and passion for AI and ML-driven value creation. You will lead WovenLight teams from a business and commercial perspective across two types of projects:

• Diagnostic projects — evaluating the value creation potential at target or portfolio companies, identifying where AI/data science can unlock meaningful performance improvement
• Deployment projects — executing on identified opportunities using WovenLight's deep AI/ML capabilities inside portfolio companies

The role is fast-moving and context-dependent. Across all projects, Deployment Strategy Principals are expected to lead on:

• Scoping and leading successful projects — both pre-acquisition diagnostics and post-acquisition execution
• Stakeholder management and communications — across multiple levels within a portfolio company and with one or more PE sponsors
• Leading change management activities at portfolio companies — overcoming the typical last-mile challenges of user education and adoption
• Supporting portfolio companies with broader analytics and AI topics — including organisational and operating model decisions
• Tracking the impact of WovenLight's work and attributing clear financial value creation

We invest across a range of sectors — with current focus on Services, Industrials, Healthcare, and Consumer & Sports. Domain expertise in one or more of these sectors is valued, though we are interested in strong candidates from adjacent industries where the commercial and operational fundamentals translate.

Examples of projects you could work on include:

• Helping a company and its sponsor position for sale by creating a roadmap of future AI/data value creation opportunities (sell-side diagnostic)
• Leading rapid evaluation of ML/AI value creation potential at a target company (buy-side diagnostic)
• Optimisation modelling to improve manufacturing throughput
• Predictive modelling to anticipate and avoid asset downtime
• Demand forecasting and supply chain optimisation
• Predicting and reducing customer churn
• Identifying next best action for sales agents
• Geospatial modelling to improve store or asset footprint

What We're Looking For

Business Leadership & Stakeholder Management

• Proven experience leading commercial transformations (4+ years) with a strong track record of driving adoption of new technologies or processes
• Exceptional stakeholder management skills, including experience educating senior leadership on the value of data and analytics initiatives and winning hearts and minds across organisations
• Change management expertise with a demonstrated ability to drive organisational adoption
• Business acumen with strong commercial understanding gained as an Engagement Manager at a consulting firm, Product Manager at a technology company, or in a similar commercially focused role

Commercial & Financial Acumen

• Strong business understanding spanning multiple industries and value chain functions, enabling you to identify and articulate value creation opportunities
• Financial literacy including familiarity with investing and corporate finance principles, allowing you to work effectively with commercial professionals and quantify the financial impact of initiatives
• Ability to measure, track, and communicate the business impact of analytics and AI deployments — including clear attribution of financial value created
• Domain experience in one or more of our target sectors — Services, Industrials, Healthcare, or Consumer & Sports — is an advantage

Technical (ML, AI, Software Development) Understanding

This is not a hands-on technical role, but Deployment Strategy Principals must have a strong, practical understanding of key AI and ML concepts — enough to guide technical teams, evaluate opportunities, and ensure business impact. As part of our selection process, we will expect candidates to be able to answer questions such as:

• What is meant by a "data pipeline"?
• What's the difference between a Data Engineer and a Data Scientist in the context of an ML development and deployment workflow?
• What is meant by "overfitting" in a model?
• What is a "feature" in machine learning? What is feature engineering?
• What is an A/B test used for in analytics or ML?
• How does a generative AI project using a pre-trained model differ from a traditional ML project?
• Why might a technically excellent ML model still fail to deliver business impact?

Our core team is based in London. Interviews for this role will be conducted via a combination of phone, video-conference and in person.

WovenLight is committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation, gender identity or any other basis as protected by applicable law.