Deployment Manager
London
Deployment /
Full-time /
On-site
WovenLight is creating a new category of investment firm. We combine traditional private equity investing with deep capabilities in AI and machine learning - in order to drive outsized value creation at our portfolio companies.
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 and across sectors, we focus on companies where there is untapped potential from ML/AI/data science.
During H1 2025, WovenLight has:
- Executed on our first two deals - partnering with leading PE firms to co-sponsor investments. For more details, please see our current portfolio at https://www.wovenlight.com/portfolio
- Entered into a strategic partnership with leading European PE firm – Altor. Through this partnership, WovenLight acts as an AI transformation partner to Altor and its portfolio companies. For more details, please see https://www.wovenlight.com/perspectives/altor-advances-ai-leadership-through-a-strategic-partnership-with-wovenlight
To execute our mission we are building an integrated team of world class data, investment, technology and operations professionals.
Role overview
WovenLight Deployment Managers are commercially focused project leaders who have expertise and passion for AI and ML driven value creation. They join WovenLight teams to support key business/commercial workstreams as we deliver two types of projects. i) Diagnostic projects that evaluate the value creation potential at target companies / portfolio companies. ii) Deployment projects that execute on the identified value creation opportunities using our deep AI/ML capabilities
The role is fast-moving, varied and context dependent but on all projects, it is likely that our Deployment Managers are involved with:
- Scoping and leading successful projects – both pre-acquisition diagnostics and post acquisition execution projects
- Stakeholder management and communications – often across multiple levels within a portfolio company; and one or more sponsors/owners
- Driving change management activities at portfolio companies – overcoming typical ‘last mile’ challenges of user education/adoption
- Supporting portfolio companies with wider analytics and AI topics (e.g. organisation/operational model decisions)
Examples of projects you could work on include:
- Helping a company/sponsor position for sale by creating a roadmap of future AI/data value creation opportunities (Sell side diagnostic)
- Leading rapid ‘outside in’ evaluation of value creation potential at a target company (Buyside diagnostic)
- Optimisation modelling to improve manufacturing throughput (Deployment)
- Predictive modelling to anticipate/avoid asset downtime (Deployment)
- Predicting and reducing customer churn (Deployment)
- Identifying next best action for sales agents (Deployment)
- Geospatial modelling to improve store footprint (Deployment)
Capabilties and experiences
Business Leadership and Stakeholder Management
Experience of analytics focused engagements, in particular those involving ML/AI driven value creation
Strong stakeholder management skills including experience educating non technical audiences on the value of data/analytics initiatives and winning hearts and minds across organizations
Change management skills with a demonstrated ability to drive organizational adoption
Business acumen with strong commercial understanding, perhaps gained from experience as Junior Engagement Manager within a consulting firm, Product Manager at a technology company, or similar business-focused role
Commercial and Financial Acumen
Strong business understanding 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 investment colleagues and quantify the financial impact of initiatives
Interpersonal and communication excellence supporting your ability to build and maintain relationships with senior stakeholders across organizations (portfolio companies, investors, partners)
Technical (ML, AI, Software Development) Understanding
While this is not a hands-on technical role, Deployment Managers at WovenLight 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 those listed below. These examples are not an exhaustive list, but they illustrate the baseline level of ML/AI fluency we expect from applicants who will be responsible for unlocking business value from these technologies.
- What is meant by a “data pipeline”?
- What’s the difference between a Data Engineer and a Data Scientist in the context of a machine learning 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 the typical workflow for a generative AI project using a pre-trained model (like OpenAI’s GPT) differ from a traditional machine learning project?
- Why might a technically excellent machine learning model still fail to deliver business impact?
Please note: We are not seeking new agency relationships at this time.
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.
