About the company
Public is an investing platform that allows people to invest in stocks, ETFs, treasuries, crypto, art, collectibles, and more – all in one place. Public’s platform helps people be better investors with access to custom company metrics, live shows about the markets, and real-time analysis. Members control how they invest with a suite of powerful tools, and get insights from a community of millions of investors, creators, and analysts. Since 2019, Public has raised over $300 million. Investors include Accel, Tiger Global, Will Smith's Dreamers VC, The Chainsmokers' Mantis VC, and Shari Redstone's Advancit Capital, as well as renowned figures in business and culture, like Maria Sharapova, Tony Hawk, and NYU Stern professor Scott Galloway.
Job Summary
What you’ll do:
📍Lead a team of high performing Data Analytics Engineers, ensuring proper execution of functions; foster a positive team culture and set data management standards and best practices 📍Develop an in-depth understanding of our business goals, priorities, and success metrics in order to help set business strategy, build data solutions for complex problems, and inform decision-making 📍Work within large datasets to conduct analyses – that includes: data science, exploratory data analysis, and model development – and then clearly communicate results / insights to leadership 📍Build and manage all advanced reporting, dashboards, data models, and tools to support cross-functional teams and initiatives, and enable teams to self-service where possible 📍Extract, manipulate, cleanse, and synthesize data from a variety of sources through ETL technologies
You’ve got:
📍8+ years of experience in algorithmic engineering, data science, or machine learning, and 5+ years in people management and scaling teams; strong technical domain knowledge is required in order to coach and grow the team (this includes mastery of at least one programming language and SQL) 📍Passion for all things artificial intelligence and machine learning, and some experience working with Generative AI (GenAI) 📍Ability to collect required data from internal and external systems, design data storage structures, and build automated data pipelines that are reliable and scalable in a fast-growing data ecosystem 📍A strong understanding of data modeling principles and modern data platforms to build data model architecture, data ETL processes, reporting, and analytics solutions 📍The ability to push the boundaries of analytical insights with modern machine learning and data science stacks (including AWS, Python, Pyspark) and expertise with Fivetran, Snowflake, DBT, and Looker 📍Exceptional communication skills, high EQ, and the ability to manage multiple projects across stakeholders in a fast-paced environment 📍Preferred: Experience with large-scale consumer products at start-ups or within fast growing finance or technology companies 📍Bonus: An advanced degree in Statistics, Econometrics, Mathematics, or a related quantitative field
