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- Tasks: Lead AI initiatives to boost efficiency and revenue across portfolio companies.
- Company: Join a global private equity fund focused on innovative value creation.
- Benefits: Enjoy flexible remote work options and opportunities for international travel.
- Why this job: Be at the forefront of AI transformation, collaborating with top executives in a dynamic environment.
- Qualifications: 10-15 years of experience in AI, with proven leadership in operational settings.
- Other info: This role offers a unique chance to shape the future of multiple businesses.
The predicted salary is between 43200 - 72000 £ per year.
Working for a Global Private Equity fund, this newly created AI Specialist role will be a core member of the Portfolio Value Creation team, working directly with both C-suite and technical leadership of multiple portfolio companies. The role is both strategic and hands-on, requiring the ability to identify and execute AI and automation initiatives that deliver measurable value for portfolio businesses across multiple sectors.
Key Responsibilities:
- AI-Driven Value Creation: Identify, prioritize, and deliver AI/ML use cases that drive value through efficiency gains, revenue growth, or enhanced decision-making across portfolio companies.
- Automation as a Value Lever: Define and implement automation opportunities to enhance operational scalability.
- Strategic Partnership: Collaborate closely with C-suite executives and technical leaders in portfolio companies to ensure alignment and successful implementation of AI and automation efforts.
- Execution Model Management: Deliver projects through a hybrid model involving hands-on delivery, coordination with external vendors, and oversight of internal and portfolio-based technical teams.
- Capability Building: Support the development of internal AI/automation capabilities within portfolio companies, including team building, skill development, and change management.
Job Requirements:
- 10-15 years total work experience. Proven track record of delivering AI-driven value in operational business settings.
- Hands-on leadership of in-house AI/data science teams, including capability build-up, execution, and cross-functional alignment.
- Deep understanding of AI/ML strategy and implementation — including automation, model deployment, and business integration.
- Strong ability to engage and influence C-suite and technical leaders in transformation-focused environments.
- Ability to work in Central London, with flexibility for remote work and ad-hoc international travel.
Contact Detail:
The Barton Partnership | B Corp™ Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Specialist - PE Value Creation - London
✨Tip Number 1
Network with professionals in the private equity and AI sectors. Attend industry events, webinars, or meetups to connect with C-suite executives and technical leaders. Building these relationships can give you insights into the role and potentially lead to referrals.
✨Tip Number 2
Stay updated on the latest trends in AI and automation. Follow relevant publications, blogs, and thought leaders in the field. This knowledge will not only help you in interviews but also demonstrate your passion and commitment to the role.
✨Tip Number 3
Prepare to discuss specific AI/ML use cases you've implemented in previous roles. Be ready to explain how these initiatives drove value and improved decision-making. Real-world examples will showcase your hands-on experience and strategic thinking.
✨Tip Number 4
Familiarise yourself with the portfolio companies of the fund you're applying to. Understanding their business models and challenges will allow you to tailor your discussions and demonstrate how your skills can directly benefit them.
We think you need these skills to ace AI Specialist - PE Value Creation - London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI and automation. Focus on specific projects where you've delivered measurable value, especially in operational settings. Use keywords from the job description to align your skills with what the company is looking for.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about AI and how your experience aligns with the role. Mention your ability to engage with C-suite executives and your hands-on leadership style. Be sure to include examples of successful AI initiatives you've led.
Showcase Your Technical Skills: If applicable, include a section in your application that details your technical skills related to AI/ML. Highlight any specific tools, programming languages, or methodologies you are proficient in, as this will demonstrate your capability to execute the responsibilities outlined in the job description.
Prepare for Potential Interviews: While this step is not part of the written application, it's important to prepare for interviews by thinking about how you would discuss your past experiences. Be ready to explain your approach to identifying AI-driven value creation and how you've successfully implemented automation in previous roles.
How to prepare for a job interview at The Barton Partnership | B Corp™
✨Showcase Your AI Expertise
Be prepared to discuss your previous experience with AI and machine learning projects. Highlight specific use cases where you've driven value through AI initiatives, as this role requires a deep understanding of AI/ML strategy and implementation.
✨Demonstrate Strategic Thinking
Since the role involves working closely with C-suite executives, it's crucial to showcase your ability to think strategically. Prepare examples of how you've aligned AI initiatives with business goals and how you can contribute to the overall value creation for portfolio companies.
✨Prepare for Hands-On Scenarios
Expect to discuss hands-on experiences in leading AI/data science teams. Be ready to explain how you've managed projects, coordinated with vendors, and built internal capabilities. This will demonstrate your practical knowledge and leadership skills.
✨Engage with Real-World Examples
During the interview, use real-world examples to illustrate your points. Discuss specific challenges you've faced in implementing AI solutions and how you overcame them. This will help you connect with the interviewers and show your problem-solving abilities.
