So You Want to Work in Political Data

Are you someone with technical skills who is interested in politics and wants to make a positive impact? Political data could be a great fit for you! Here’s an overview to introduce you to different career opportunities in the field of political data.


First thing first: what do I mean by political data? I’m using “political data” to refer to the use of data in electoral politics. This mainly means data that is used to understand how and why people will or won’t vote. In the realm of campaigns, political data is used to try to ensure that, come election day, your candidate will get the most votes. In an increasingly data-driven world, campaigns are eager to use data to gain advantages over their opponents, and the effective use of political data can make or break a campaign.


There is a huge range of political data-related skills and jobs out there. For the purpose of this brief introduction to the field, I’m going to keep it simple and focus on a few broad categories. Disclaimer: this blog post is not exhaustive and greatly simplifies the

wealth of data-related opportunities in the political space.



TYPES OF DATA ROLES


Political data scientist: Data scientists are the ones doing the intense research in the electoral space. They’re on the cutting edge of analyzing all the data that’s out there and understanding how it turns into votes. For example, data scientists in electoral politics build models to predict partisanship, turnout, and issue support of individuals based upon their characteristics. Most campaigns don’t have the time or money to hire their own data scientists, so data scientists typically work within other organizations, like private firms or party organizations, and the output of their models (often referred to as “scores”) are then purchased or provided to campaigns through services like NGP-VAN.


Political data analysts: Political data analysts take the information that’s available, like the voter file, census data, historical voting results, and scores from models, and make it actionable. They identify useful information hidden in the data that can inform strategy and actions, like knowing which voters to target with what information, where to focus turn-out efforts, or whether to contact someone via direct mail or Facebook ad. Data visualization and communication are often a big part of this process, as data analysts need to make their findings easy to understand and actionable for campaign teams. This is the bucket that Bluebonnet Data fellows mainly fall into.


Political tech developer/engineer: Political tech is adjacent to political data and often overlaps, so I’m including it in this round up. Political tech refers to the technology used to win votes. There’s been a surge in political tech startups that offer various services and software to make every aspect of campaigning easier: fundraising, volunteer mobilization, budgeting, digital organizing—you name it, there’s probably a tech tool that can help you. Many of these tech tools are developed by progressive startups, but some well funded campaigns or organizations may build out their own in-house tools.



WHERE POLITICAL DATA JOBS EXIST


Now that we’ve established some broad political data roles, where can you find those jobs? I’m going to break the political data landscape into three categories: Campaigns, Democratic Infrastructure, and Industry.


Campaigns: At the most granular level, we have campaigns.


Campaigns vary greatly in financial and human capital. A candidate running for school board may be a one-person show. A candidate running for US President has a full blown national organization. Data isn’t viewed as an essential for a small campaign. Typically, hiring a campaign manager, field director, finance director, communications director, etc., takes precedence over a data director. If you’re looking to be hired as a data analyst for a campaign, your best bet is to look at well-funded congressional races and higher, as smaller operations will likely not have an in-house data team.


Pros: You’re really in the thick of things, the work is high-stakes, you get to work with passionate people, and you can have a lot of independence and impact.


Cons: Typically long hours, often structure is lacking, pay is variable, no long-term job security, and fewer resources.


Democratic Party Infrastructure: At the next level up from campaigns in the Democratic Party Infrastructure. This includes state parties, Democratic Legislative Campaign Committee (DLCC), Democratic Congressional Campaign Committee (DCCC), the Democratic National Committee (DNC), and more. These groups exist to support Democratic candidates and typically have more resources, structure, and a longer-term, bigger picture vision.


Democratic Party organizations use data analysts to help set party strategy and aid candidates. This might start with doing district analyses to decide which races to invest in or supplying candidates who can’t afford their own data teams with win number estimates and other assistance. Democratic Party organizations also sometimes hire data scientists to do more in-depth research, such as creating a custom partisanship score for their state.


Pros: There’s theoretically more infrastructure, more resources, bigger picture planning, you get to help a lot of different campaigns, there’s potentially better pay than a campaign, and possibly more job security.


Cons: You’re one step removed from campaigns, and there’s often more bureaucracy and less independence.


Industry: Beyond campaigns and party infrastructure, there are a lot of other organizations that have sprung up around electoral politics. I’m grouping these as “industry” but there are many subgroups. For example:


  • Consulting companies: These are the organizations that have the most resources to do intensive research. Often these companies are the ones who hire data scientists to build algorithms and sell the scores. Most of these are for profit companies and are able to offer more competitive salaries.

Examples: Civis Analytics, BlueLabs Analytics, Catalist


  • Advocacy groups and PACs: This category includes groups who have an interest in seeing voters elect a certain candidate or elect a category of candidates, such as candidates who support women’s reproductive rights. These groups may hire political data analysts to help their own efforts in promoting candidates or certain voting preferences.

Examples: Senate leadership PAC, EMILY’s List, Planned Parenthood Action Fund


  • Civil rights orgs: This group includes organizations that are typically non partisan but focus on topics like voter registration and voter enfranchisement. Some of these use data analysts as a secondary tool to support their missions, while others may have an explicit data focus, such as using data to analyze gerrymandering or find unregistered voters.

Examples: CiviTech, Metric Geometry and Gerrymandering Group


  • Political tech startups: There are a large number of political tech startups addressing the challenges of campaigning with innovative solutions. Many of these startups offer software as a service, such as helping campaigns contact voters or organize events, but there’s a wide range. This subgroup is where you’ll find most developers. Higher Ground Labs is progressive political tech accelerator that has helped launch many of these startups.

Examples: Higher Ground Labs portfolio companies like Mobilize and OutVote


Pros: Industry jobs can offer more competitive salaries, particularly in the private sector, with more infrastructure and resources. Issue-focused organizations can let you dig deep into working for specific issues you care about, while startups provide a fast-paced, exciting work style.


Cons: For-profit companies might feel less mission-driven. Non-partisan organizations face restrictions about the exact type of work that can be done in the electoral politics space. Typically industry jobs are more removed from being directly involved with helping progressive candidates win.



RESOURCES TO GET A JOB IN POLITICAL DATA


Educational resources: To get a job in political data, it’s helpful to learn more about political data and build out skills.

  • Check out our Bluebonnet Blog for a few resources on learning how to code in general.

  • Arena Academy runs periodic programs to train campaign staff. One of their tracks is for data directors.

  • FiveThirtyEight is a great resource for staying informed on politics with a data-driven perspective and examples of how data can be used in electoral settings.

  • Change The Game offers trainings for data in the progressive space focused on targeting and data management.

  • The Bluebonnet Data Fellowship provides training for people who have technical backgrounds but want to learn how to apply them to the political space. Our applications open periodically, so be sure to apply or sign up to be notified when they open.


Job boards: Actively looking for a job? Check out the posts on these boards.

  • All Hands is working to match data and tech professionals with progressive organizations that have job openings.

  • Arena, in addition to its Academy, also maintains a job board to power campaigns and organizations.

  • Higher Ground Labs maintains a job board for its portfolio companies.


Progressive data communities: Getting to know more people in the progressive data space is a great way to get involved or find a job.

  • Rewriting the Code is a community for women in tech.

  • Coding it Forward is empowering the next generation of technology leaders interested in social impact (they also have an internship program!).

  • And last, but certainly not least, Bluebonnet Data. Once you become a Bluebonnet fellow, you’re part of the Bluebonnet family. We’re building a community of progressive, talented people who want to make an impact with their skills.


Did we miss something? Let us know in the comments!



ABOUT THE AUTHOR: Danielle Strasburger is one of the founders of Bluebonnet Data. She's passionate about building people power for progressive causes.

© 2020 by Bluebonnet Data    |    info@bluebonnetdata.org

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