Description

Director of Data Analytics, Business Analytics & Strategy

About LFC

Legacy Franchise Concepts, a partner of Prospect Hill Growth Partners, invests in health, wellness, and lifestyle brands across the franchise landscape. Our portfolio includes SweatHouz, the fastest growing infrared sauna and cold plunge franchise, and Dogtopia, the leading provider of dog daycare in North America.

What to expect

The business Analytics & Strategy team’s mission is to enable a data-driven business and supercharge growth across our portfolio of companies. This newly designed team is responsible for providing insights to department leaders regarding customer acquisition, revenue generation, cost-cutting, and ways to optimize service fulfillment. The team directly supports leaders from our retail locations and the executive team of shared services at LFC.

The business Analytics & Strategy team will also oversee due diligence for all new brand acquisitions.

Reports to: COO

Who is right for the role

You are a hands-on senior data analyst and/or scientist with strong business acumen looking to lead a cross-functional and cross-product data team. You thrive in ultra-high growth, high-ambitious organizations who put finding the right answer to a problem, above any single person being right.

You are a collaborative leader with expert-level experience with leveraging modern data stacks and techniques to drive business process automation and support revenue growth and process optimization. As a player coach, you will build the foundation of our data strategy, and work cross functionally with other leaders.

You enjoy tackling hard problems by mapping out the entire data lifecycle and turning insights into actionable business strategies by interacting with field leadership.

 What you will do

• Work with Analytics & Strategy partners to provide actionable insights to department leaders, fostering revenue growth, cost reduction, and service optimization.
• Contribute to all stages of the business analytics & strategy process: translating a complex business problem into a data engineering, data analysis, business intelligence roadmap, and interacting with key stakeholders
• Drive the company’s data strategy: the tech stack, data infrastructure & architecture & governance
• Build business intelligence for all divisions of the organization to provide a compass for business growth
• Be a player-coach, ready to get your hands dirty and help with all stages of the data science projects
• Oversee Analytics & Strategy partners, so they develop and maintain complex pipelines & databases for all business units, clean data, and build models
• Develop probability analysis models for performance marketing to forecast and optimize for optimal CAC and ROAS
• Lead and execute on all things building and validating models, putting them into production (data visualization), and building the business intelligence for field leaders
• Oversee the production of all weekly, monthly, and quarterly performance reports
• Interact with stakeholders, including but not limited to: field leaders, C-suite, private equity, board of advisors, potential acquisitions
• Act as the primary liaison with 3rd party software providers for all things data
• Co-lead the data room for due diligence of all potential acquisitions

 Qualifications:

• MS or 4 years of equivalent experience in a quantitative field (computer science, engineering, mathematics, business analytics, statistics)
• Demonstrated leadership in data analytics, performance marketing analytics, data strategy development, and business intelligence implementation, with effective communication skills at the executive level.
• Proven track record of extracting data insights and managing databases, specifically in business analytics
• Expert-level skills in SQL, Python, and standard data science libraries; familiarity with data visualization tools like PowerBI or Tableau.
• Proficient with data wrangling and analyzing large datasets in structured and unstructured formats
• Strong understanding of creating and managing API from data sources
• Strong business acumen and in-depth data science skills
• Ability to think from first principles, and manage/prioritize multiple projects

Interview process

1. Screening call with COO
2. Technical project which includes testing all stages of data engineering and science projects
3. Team meeting
4. Reference checks
5. Offer