We're on a mission to provide every human being with access to economic opportunity. Avala is looking for world-class talent ready to tackle challenging projects that will ultimately enable a more abundant economic future for all humanity.

We’ve raised several millions of dollars in funding of venture capital, from Valor Equity Partners, Flybridge Capital, Wonder Ventures, Draft Ventures, MaC Ventures, and many other high profile investors. Happy to tell you how much over the phone. We are a post-Series Seed company.

Data is deeply embedded in the product and engineering culture at Avala. You will be joining Avala's small and elite team of engineers, and will own our data analytics tooling and the infrastructure that runs it all. You will help other engineers and the entire company through direct support by doing data analysis for them as well as through the applications and tools you build so they can self-serve those analyses in the future.

If you join us, you will have a central role in empowering the entire team to better leverage the vast amounts of data we collect. Your contributions will have an outsized impact toward Avala's mission of enabling a future abundant economic opportunity for all.

We are looking for a talented Data Scientist & Engineer to join us as a foundational member of the team to provide leadership in the definition and implementation of processes and tools to enable data science at Avala. This is an opportunity to have a big impact and get lots of ownership. We're looking for someone who thrives in the very early stages of a company and is self driven.

You will:

Work with stakeholders to take a vague problem statement, refine the scope of the analysis, and use the results to drive informed decisions Write reproducible data analysis over data using cutting-edge open source technologies Summarize and clearly communicate data analysis assumptions and results Build data pipelines to promote your ad-hoc data analyses into production dashboards that engineers can rely on Design and implement metrics, applications and tools that will enable engineers by allowing them to self-serve their data insights Work with engineers to drive usage of your applications and tools Write clean and tested code that can be maintained and extended by other software engineers Operate and support your production applications Keep up to date on relevant technologies and frameworks, and propose new ones that the team could leverage Identify trends, invent new ways of looking at data, and get creative in order to drive improvements in both existing and future products

Competitive compensation and equity package Free base medical, dental, and vision insurance plus free membership to One Medical 401k program 21 PTO days per calendar year + sick days when you need it Annual professional learning and development budget Work from home equipment stipend Flexible in-office policy when we return Quarterly socials and recharge days Autonomy to make decisions in a rapidly growing environment

We encourage any candidate who meets 70% of these qualifications to still apply!

Strong software engineering foundations and a desire to apply those skills toward making other engineers more productive Must be willing to constantly learn new things. Passionate about joining a small team and building a company. Strong proficiency in Python, SQL Strong foundation in statistics Experience building data visualizations Experience writing software in a professional environment Strong verbal and written communication skills Strong problem-solving skills to help refine problem statements and figure out how to solve them with the available data Smart but humble, with a bias for action

Nice to haves:

You've worked at a startup before. A history of working on side/hobby projects and contributing to open source projects is a plus. Experience with data science tools such as Pandas, Numpy, R, Matlab, Octave, Jupyter notebooks, Bokeh, Superset and Airflow Experience building data pipelines Experience building web applications Experience building machine learning models in a professional environment Experience with continuous integration and continuous development Experience in devops, e.g. Linux, Ansible, Docker, Kubernetes Experience with Scala Understanding of distributed computing, e.g. how HBase, HDFS, Spark and Presto work