Role Description UP.Labs is seeking a proven Head of Data with a track record of scaling technical teams in a 0-to-1 Environment to lead a ML-based product in the aviation space rapidly scaling within our portfolio - leveraging simulation, recommendation engines and optimization. As our Head of Data within this portfolio organization you'll be leading and developing best practices for data identification, capturing, modeling, testing, and deployment. You'll also have access to the UP.Partners ecosystem - an expansive team across product, engineering, design, analytics, marketing, legal, talent, finance, and venture capital available to help advise & scale the portfolio organization quickly. In this role you will:
- Immediately step into a business built for success - quickly utilizing the UP.Ecosystem for advisory and connections, work directly with a highly qualified CEO and corporate partner closely invested in the success of this org., and manage an already-established product market fit; harnessing our proven & strict methodology to potentially achieve quick and long-term wins.
- Oversee and lead the data org; leading with a hands-on approach to building processes & playbooks, recruiting your team, setting goals, strategy alignment, and managing expectations with internal teams, corporate partners, investors, and UP.Labs.
- Establish data science, engineering and advanced analytics as an organizational capability
- Design, construct, and manage the data architecture, including data warehouses, data lakes, and data pipelines
- Oversee data privacy and security protocols to ensure compliance and safeguard sensitive information.
- Direct the application of machine learning to our product and service offerings
- Hire, retain, and mentor a world-class team consisting of diverse skill-sets; enhance employee performance via evaluation and coaching.
You should have:
- 8+ years experience within data science, machine learning and data engineering, with 5+ years of experience leading, developing, and scaling data teams
- Success as a cross-functional people manager of an operationally complex, high-growth environment with an ability to be hands-on while allocating resources correctly.
- Hands on experience with machine learning algorithms like linear and logistic regressions, XGBoost, random forest, and anomaly detection algorithms for building, evaluating, deploying and monitoring ML models from scratch.
- Leadership experience; preferably early-stage, venture backed growth companies specifically within aviation, schedule planning, route optimization, fleet management or logistics
- Experience working in hyper-growth start-up ventures, preferably as an early-stage leader
- Extensive knowledge of data architecture, including data warehouses, data lakes, and pipelines
- Experience with Databases, Data Warehousing, and ETL systems and solutions, e.g. Oracle, DataBricks, Snowflake, and respective public cloud service offerings from AWS, GCP, and Azure.
- High EQ and low ego; you carry an executive presence regardless of years of experience.
- You've helped to recruit and retain world-class talent, while developing a values-oriented, high-performance culture.
- Exceptional collaboration, communication, and leadership skills.
UP.Labs Summary: We build high-growth technology startups that enable faster, cleaner, and safer movement of people and goods. Our vision is to transform the moving world by pairing leading corporations and entrepreneurs with a proven methodology for launching and scaling software and hardware companies. Our platform is unique in three ways:
Risk: We reward our entire team and ecosystem of partners with meaningful equity Technology: We build and launch scalable technology products that form the basis for each venture Industry Focus: We stay focused on the underlying fabric of retail mobility We work with corporate investors over a multi-year period to launch a portfolio of ventures. Our team is dedicated to the first year of a new venture's life cycle: from ideation to minimum viable product build - and beyond.