Senior Data Scientist Lead at Civic Eagle

We are seeking a Senior Data Scientist to lead development of cutting edge insights into legislative & public policy data. Our Data Insights team researches and develops AI techniques that help our customers cut through the fog of complex legislative data to see clearly where and when they can take action for better policy outcomes. Lawmaking often looks like information warfare; we seek to level the playing field through the delivery of accessible, automated data insights. Imagine a community advocacy group operating with a limited budget to navigate within that environment: the insights you develop could mean the difference between that group's members exercising their voice on that issue, or missing the chance.
You will collaborate with data engineers, domain experts and product leadership to design data experiments, de-risk ideas, and drive those ideas into product-ready insights. This is a chance to technically lead a new team, mentor teammates, and build a culture of effective collaboration around deep domain knowledge, product strategy, and execution. This is an individual contributor role that reports to the CTO, with an option to move into people management in the future.
Glimpses into our data:

Hundreds of thousands of proposed laws (bills) across many years in the US Congress, 50 state legislatures (plus DC and Puerto Rico)
A set of actions and documents related to each bill that are added over time: help our users identify which bills are moving/important and which are not
Bill text that might be reintroduced between years, or inserted into other (ostensibly unrelated) bills: help our users catch these cases where important language appears and re-appears
Bill text can be hundreds of pages for a single bill: help our users identify key entities, topics, and more

What you will do:

Research and develop data insights using statistical, machine learning (ML) and natural language processing techniques (NLP)
Strengthen our experimental process, with an emphasis on quickly de-risking high level data insight ideas by using best practices for data science experimentation and a product mentality
Contribute to a culture of effective collaboration around deep domain knowledge by diving into the domain with research-like curiosity and mentoring teammates

The right person for this role:

Has 3+ years of experience in data science roles
Has a strong understanding of data science experimentation and foundational topics / best practices: 

data fundamentals: exploratory data analysis, data augmentation, data split and versioning etc.
model fundamentals: translate a problem / question into a model, model training,  parameters tuning
evaluation fundamentals: error analysis, metrics, statistical significance
communication: documentation, charts, presenting insights to audience at different level of technical debt

Has familiarity with the data science stack: 

Python
SQL
scientific computing libraries (numpy, pandas, scikit-learn etc.)

NLP experience is a huge plus: for example familiarity with modern NLP (e.g. spacy) or deep learning libraries (e.g. hugging face). Alternatively, eager to learn NLP and happy to work towards that.
Is passionate about solving problems for people doing world-changing work. Knowledge of legislative domain is a plus, but curiosity is a must
Brings a product mentality: research is a tool to drive high-risk/high-reward value into the hands of real users
Upholds our company values: We put people first. We believe in transparency. We are audacious thinkers and doers.
Has experience and willingness to work in a remote-first, distributed team.
Gets excited about delivering tools that truly move the needle for people who do important, world-changing work.
Believes that diversity and communication are core strengths in an engineering team.
Wants to join a startup at the stage where culture is being actively established and engineering habits are being molded.
Cares about civic engagement and the health of our democracy.

Salary Range
Salary depends on location and experience. If you are closer to 3 years of experience, expect a range from $153K to $191K (depending on location). If you are closer to 6-10 years of experience, expect a range from $185K - $230K (depending on location).
To set compensation, we use market research and a defined career advancement ladder. Our goal is to make the compensation scale equitable inside the company, rather than being driven entirely by ad hoc negotiation (which can be a vector for bias). This is certainly a challenge in the engineering market, but one we welcome in service of one of our core values: transparency.