Lead Data Scientist

Job Description: As the Lead Data Scientist at UP.Labs, you'll get to play a key and unique role in building new startups from 0 to 1 and creating practical outcomes from emergent technologies and sophisticated data. You'll act as the principal domain hands-on expert and owner of data science for a technology venture. You will collaborate with our venture teams to drive both high-level and day-to-day analysis data engineering overview. This includes everything from assisting in validating the initial business concepts, validating data use cases, developing proof of concepts, and working closely with the product and engineering team members to drive practical outcomes. You’ll have the support you need to drive new innovation in impactful domains ripe for change and growth and be at the forefront of creating a more intelligent industry. In this role, you will: Act as the primary owner of Data Science, Analysis, and Data Engineering as a subject matter expert. Build out a team and incubate expertise amongst several venture start-ups. Design and deliver impactful solutions to complex problems, using code, manual research, or intelligence-driven analysis. Create rapid proofs of concept, then scale into functional MVPs to turn concepts into tangible reality. Mentor and support effective teams to achieve bigger outcomes at a greater scale in data density and system complexity. Cross-pollinate learnings, best practices, and insights between multiple ventures to drive continuous improvement of Engineering and Data Science at UP.Labs. Enjoy working in a diverse, dynamic, collaborative, transparent, and inclusive environment where all ideas and opinions are equally valued. You should have: 5-8+ years experience within Data Science, Data Engineering, and Machine Learning domains and their practical applications. Familiarity and preference for working in ambiguous, fast-paced environments such as startups and growth-phase tech companies. Hands-on and end-to-end product build, development, and delivery experience. Experience working with or managing remote, distributed teams including full-time engineers and vendors/contractors. Awareness of the latest in Data Science and Data Engineering trends, as well as new use cases within the ML Space. Experience working with agile, lean, and Continuous Delivery approaches, such as Continuous Integration, TDD, Infrastructure as Code, etc. Experience working with cloud-native software architectures. Strong experience in collaborating with Product teams to find effective solutions. Strong communication skills put to use by explaining technical vision and deeply technical concepts to a variety of multidisciplinary team members. An open, curious, and humble mindset that builds on to our open, inclusive, and collaborative environment. Additional desired competencies: Experience with RDBMS, Data Warehousing, and ETL systems and solutions, e.g. Oracle, Data Bicks, Snowflake, and respective public cloud service offerings from AWS, GCP, and Azure. Experience with systems planning in the domains of transportation, aviation, or digital simulation would be valuable. Location:

San Carlos, CA Working Model:

Onsite - Monday-Thursday; Remote - Friday 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 society mobility and transportation. We work with corporate investors over a multi-year period to launch a portfolio of mobility-focused 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) to recruiting and hiring the full-time team who will scale the business. We rapidly ideate concepts from scratch and vet them for early indicators of product-market fit.

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