New York City (Preferred), Open to US
Cybersyn is a new DaaS (data-as-a-service) company. Cybersyn’s mission is to make the world’s economic data transparent to governments, businesses, and entrepreneurs and enable a new generation of decision makers. We acquire unique data assets (companies, licenses, data rights, consumer dividends) and build derived products on top of that, focusing on measuring what consumers and businesses are spending money on. You can think of Cybersyn as a cross between an investment firm and a technology company focused on data: if we are successful, we will disrupt the likes of Nielsen and S&P (~100bn market cap). The reward is great - if we are successful, we can disrupt an industry worth $100Bs and build SimCity for the real world.
What we need:
- Experience in Python and Python-based data visualization libraries
- Our stack here is Streamlit + Vegalite
- SQL should be a core competency
- Window functions, common table expressions, and pivots should excite you!
- Basic data munging skills in Python+Pandas
- Experience building interactive data documents (apps, notebooks, dashboards, etc.)
- Experience with Observable, Streamlit, Hex, Deepnote, Plotly, etc. is all a plus
- Bonus if you know Spark(/Snowpark), Snowflake, and dbt
What you will do:
- Create data visualizations in Streamlit Apps for all of our data products. Examples:
- Help automate and build monitoring systems and dashboards for costs, database provisioning, data quality, data delivery, and customer consumption
- Take end-to-end ownership of your work and enjoy working with different functions across the company
- You’ll be designing, building and testing your work – so hopefully you enjoy diving deep into dashboards. If you love dashboard products such as Opportunity Insight, FRED, or Our World In Data
What you get out of it:
- Ability to shape Cybersyn’s public facing applications and first point of contact for the majority of our customers
- Access to some of the most interesting and largest economic data in the world, including real-time spending, transaction, clickstream data from both third-party and first-party sources.
- Much of our data is not available to any other third parties.
- Our system is built with heterogeneous data sources in mind: we are not working on data from a single product or theme, but data from governments, payment processing systems (think bank records), mobile devices and apps, and SaaS exhaust (think data B2B SaaS collects)
- Fast moving culture, lots of responsibility and autonomy from day 1.
- We offer both salary & equity options in line with our funding amount. Because of our capital structure, given our current headcount, you can likely expect more salary but less equity than a startup with 4-5 people would typically grant.
- Our business model (acquiring data) requires is capital demanding, so for a startup, we have raised a significant amount of capital upfront: this means we have a unique blend of being small but having meaningful runway (will not need to raise or take dilution for 3-4 years)
- Total compensation: $100-300k