Common Networks was founded on the idea that everyone should have a choice for fast, affordable access to broadband internet. Right now, most homes in the U.S. don't, in fact 62% of homes live in a monopoly broadband market. High-speed access unlocks all the superpowers on the internet. When it works, it can be a great leveling force across the world, giving everyone access to educational tools, entertainment, immediate translations, or even medical care that they wouldn’t otherwise have.
Common Networks provides suburban neighborhoods with internet using wireless technology. We interconnect homes in a neighborhood, creating a mesh network between homes and our fiber internet sources. A whole community can then have fast and reliable internet service with only a few locations needing fiber access.
You will work closely with our Product, Engineering, Business, and Operations teams to uncover insights about how customers use our service in order to influence Product and Business decisions. You will be responsible for understanding all aspects of the business and the data available for each aspect. You will jump in and use your quantitative skills to recommend actions, and over time you will identify where more data should be collected and what areas can be most impacted by data science. As a data-loving member of the team, you serve as an analytics expert for your teammates, using numbers to help them make better decisions. This is a strategic, high-impact role that will help shape the future of product and operations.
Turn business questions into data analysis, and provide meaningful recommendations on strategy.
Build dashboards to help Product Managers & Engineers monitor performance and availability of our system.
Use data to uncover feature-usage patterns, issues with the system, potential performance enhancements, and areas to improve user experience.
Collaborate closely with Product Managers & engineers to inform product decision making with data and to identify opportunities to create more value for our customers.
Design experiments (such as A/B test), collect data, perform statistical analysis, and present solutions to senior management including executives
Answer questions from executive team for board reporting, publications, and industry reports.
Work with business planners to identify the need for new data platforms and associated product/service functionality and to propose innovative products and services that fully utilize the power of big data
Apply industry-leading ideas, research, and insights to solve complex problems or to power new business opportunities
Mentor and lead other data scientists and/or engineers as we grow the team.
Build scalable, efficient, automated processes for large-scale data analysis and machine-learning models (including development, validation, and serving).
Think creatively to find optimal solutions to our complex, often unstructured problems.
Who You Are
A hands-on leader who is willing to roll up your sleeves and discussing technical details with your team members.
Able to thrive in a dynamic environment. That means being flexible and willing to jump in and do whatever it takes to be successful.
Well organized: Ability to prioritize and deliver results timely.
An excellent communicator: Strong written and verbal communication skills, comfortable in engaging conversation with all levels.
A problem solver: Take initiatives and drive them to conclusions.
Eager to learn and implement new technologies.
Experience working at a tech company and solving real product/business problems with data
Expert-level experience working with SQL and relational data (5+ years on a regular basis)
8-10 years of relevant experience as an engineer, product analyst, data scientist, or quantitative analyst
Fluency in at least one visualization tool (e.g. Tableau, Looker).
At least 5 years experience with major programming languages such as in Java, Python, Scala
Experience with ETL design and data warehouse best practices.
At least 3 years' of experience working with large scale data in systems like AWS, Hadoop, Vertica, or others.
Background in Economics, Statistics, Industrial Operations, Math, Engineering, or CS
Nice to Haves
Experience managing a team of product analysts or data scientists