Atomic is a venture fund that founds companies. Founded in 2012, we believe that disruptive innovation is most successfully achieved by pairing innovative ideas with business discipline, and that building those ideas into businesses is not something that can be outsourced. We are engineers and entrepreneurs who build and operate the next generation of great companies.
As one of Atomic's pre-launch startups, we are building the payments stack for the modern subscription economy.
Let's get to the point. You're our data analyzer. You help us understand what's happened in the past. You will build business critical reports, set and track KPI's, and deepen our understanding of our customers.
Our customers need insights into their payments data. You provide them. You understand the care that goes into setting a well crafted metric and the challenge with doing so.
Reporting is a key part of our business, as it both an external product and an internal need. You will help us uncover what we don't know and should be looking at, propose new areas for us to analyze, and propose new sources of data for us to collect. We integrate data from multiple 3rd-party sources so you'll need to worry about the quality and cleanliness as well as coming up with useful metrics across customers.
You'll come in as the first analyst and get to stretch as far as you'd like vertically across data engineering and machine learning or horizontally, diving deep into biz ops and analytics, setting KPI's and driving our product forward.
Areas you're comfortable with:
You're familiar with turning data into insights, using languages such as SQL and Python/R to facilitate this. You've written ETL code to transform data from the application data model to something more suitable for your reporting and analysis needs, so windowing/analytic functions are part of your toolkit, and maybe even a regex or two. You also know what at the end of the day we need to see the data to deepen our understanding so you're comfortable with visualizing datasets for both internal and external customers. You've used some mix of Tableau, Mode, Looker or a comparable tool. As you deepen your knowledge of our dataset, you can help us understand whether K-Means/Mediods or DBSCAN is the right approach to clustering.
You strongly believe that action creates information.
You want to work on a small team and have lots of responsibility.
You look forward to being scrappy and enjoy overcoming challenges.
You are willing to admit when you don't know something.
We are focused on building a diverse and inclusive workforce. If you’re excited about this role, but do not meet 100% of the qualifications listed above, we encourage you to apply.
Atomic is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. Atomic considers all qualified applicants in accordance with the San Francisco Fair Chance Ordinance.
Please review our CCPA policies here.