L Catterton – Vice President, AI & Data Science

With approximately $35 billion of assets under management across nine fund strategies and 17 offices globally, L Catterton is the largest consumer-focused private equity firm in the world. Leveraging deep category insight, operational excellence, and a broad network of strategic relationships, L Catterton’s team of nearly 200 investment and operating professionals parters with management teams to drive differentiated value creation across its portfolio. Since 1989, the firm has made over 250 investments, such as Ainsworth, Bartaco, Birkenstock, Cholula, Equinox, Jio, Kodiak, Kopari, Ole & Steen, Peloton, Pinarello, Restoration Hardware, Rhone, The Honest Company, Tonal, Tula, and Zarbee’s. For more information, please visit the L Catterton website.

L Catterton is characterized by:

• A 35-year history of consumer growth investing in distinctive companies within attractive and targeted consumer categories of interest.
• Consistent and attractive risk-adjusted investment returns across all economic cycles.
• Highly differentiated deal sourcing capabilities, with a majority of the firm’s investments completed on a proprietary basis.
• Unmatched global reach and capabilities across geographies.
• An active approach to portfolio value-creation driven by an operating-centric ethos and supported by a dedicated team of operating professionals alongside a well-developed ecosystem of external resources

L Catterton’s fund strategies include:

• Flagship Buyout: Investments of $250-500mm+ in North American and Global consumer growth companies and iconic brands.
• Growth: Investments of $10-125mm in North American and European early-to-late stage consumer growth companies.
• Impact: Investments in early-to-late stage impact-oriented consumer growth companies.
• Latin America: Investments of $40-75mm+ in Latin American middle-market consumer growth companies.
• Europe: Investments of €30-80mm in Western European middle-market consumer growth companies.
• Asia: Investments of $25-150mm in Asian consumer growth companies.
• RMB: Investments of ¥30-100mm in Chinese high-growth consumer companies.
• Real Estate: Investments in global mixed-use projects anchored by luxury retail.
• Private Credit: Investments primarily in senior secured debt of private equity-backed, middle market consumer companies.

Opportunity for Impact 
L Catterton has a mission to invest in and build consumer businesses that foster deep emotional connectivity and create lasting, scalable relationships. Over time, they’ve continuously adapted their capabilities and methodologies to meet the evolving market landscape.

The Vice President, AI and Data Science will play a critical role in advancing L Catterton’s transformation into a truly AI and data-centric organization. Key focus areas include building AI and data capabilities and creating tools that drive faster, more efficient deal sourcing, enhance the rigor and accuracy of due diligence, and support a data-intensive, scalable approach to post-investment value creation.

The VP of AI and Data Science will also lead efforts to build a transformative, proprietary intelligence platform at the backbone of L Catterton’s data and AI transformation. This individual will create efficient, scalable processes to aggregate data across internal platforms, portfolio companies, web sources, and alternative data vendors, driving a step-change in our ability to leverage AI and advanced analytics across the private equity value chain. This position offers an excellent opportunity to gain in-depth insights into investment processes while collaborating with top-tier investors to create long-term value.

Role & Responsibilities

• Develop and Implement AI Applications and Analytic Reports: Contribute to the generation of insights through AI synthesis, descriptive analytics and machine learning techniques, applying data analysis and algorithm development skills.
• Lead and Enable Data Engineering and Infrastructure Development: Work closely with the team to build scalable infrastructure solutions that meet growing data needs.
• Build Data Pipelines and Ensure Data Quality: Lead and work closely with data engineers to design, construct, and maintain scalable data pipelines for efficient data extraction, transformation and loading (ETL) from diverse sources.
• Collaborate with Stakeholders: Partner with stakeholders across the organization to gather requirements for data inputs and outputs, aligning them with broader product objectives.
• Prototype and Scale Modeling Efforts: Develop prototypes and propose strategies for scaling models, including advanced machine learning for key areas such as sourcing, due diligence, and value creation.
• Partner with Product and BI Teams: Collaborate with Product, BI, and Technology teams to develop products and features that enhance the digital experience for members.

Professional Qualifications

• 5+ years in data science and machine learning, with experience contributing to team growth.
• 5+ years working with data tools and data environments including Azure Databricks, Azure Data Factory, Azure SQL Server, Power BI and Query Optimization
• Strong communicator and collaborator, able to engage both technical and non-technical audiences.
• Proficient in implementing data analytics and machine learning models, ideally within financial services.
• Experience with ETL schedulers such as Airflow, Dagster, Prefect or similar frameworks.
• Experience with utilizing web scraping tools and techniques to collect and integrate data from various online sources, ensuring compliance with legal and ethical standards.
• Familiarity with methods of training and fine-tuning large language models, such as supervised fine-tuning (SFT), knowledge distillation, policy optimization, RLHF to enhance performance and alignment with user preferences.
• Nice to have:  background in private equity or finance, with some exposure to data platform architecture.

Personal Characteristics

• Collaborative Problem-Solver: Able to build partnerships across the organization, communicate effectively, and work toward shared goals.
• Adaptable and Resilient: Comfortable with change, you view challenges as opportunities to learn and adapt, staying agile in a dynamic environment.
• Action-Oriented Self-Starter: A strategic thinker who drives execution and isn’t afraid to roll up their sleeves to get things done.
• Team-Oriented: A positive force who values teamwork, is eager to lend support to others, and makes the journey enjoyable for everyone.
• Technical Environment:
• Data Platforms: Azure Databricks, Azure SQL Server, Azure Data Factory, Azure Functions.
• Version Control Systems: Git, Azure DevOps.
• Programming Languages: Proficiency in Python and/or R; experience with high-level programming languages such as Java or JavaScript.
• Database Management: Strong SQL skills for database querying and management.
• Web Services and APIs: Experience with web services and RESTful APIs; ability to develop application prototypes to enhance data accessibility.
• Data Analytics Platforms: Familiarity with platforms like Hex or similar data analytics tools.
• ETL Tools: Proficiency with ETL tools like Apache Airflow for orchestrating data workflows.
• Data Transformation Tools: Experience with dbt (data build tool) for efficient data transformation and modeling within data warehouses.