Here's how were going to find our next teammate at the Sunlight Foundation

By Tom Lee Last Friday was Kaitlin Devine's last day at Sunlight. I got to work with her here for five years, and over that time I watched her transform from a talented engineer into the world's foremost expert on U.S. spending data. She can still write code like a champ, of course, but she also came to write congressional testimony and even enacted legislative language. We're terribly sad to lose her to GSA, but it's exciting to imagine what she'll be able to achieve from within government.Kaitlin Devine, former Sunlight software developer

I mention this because Kaitlin's story is emblematic of why I love working at Sunlight. Also, because now we need a new Kaitlin! Not to replace her (that's impossible) or even to become an expert on spending data, but to join our team of people who care about both the tech and policy dimensions of opengov problems.

We need people who understand that a CRS report and API docs can be two sides of the same coin — people who know when to push code and when to pick up the phone. Our engineers start off being great at technology and wind up as experts on Congress or procurement or lobbying or city data policies or any number of things.

There are many ways to use technology to make the world better, but I honestly don't think there's a better place to learn about how technology and government intersect.

(Also, a pretty good new taco restaurant just opened around the corner.)

If the line between wonk and geek sounds like where you want to be, we need to hear from you. You can find the full job description and application link here.

One more thing: Like a lot of software engineering shops, Sunlight has not been as successful at hiring as diverse a team as we'd like. We are continuing to work to fix this by doing specific outreach to ensure that relevant communities and candidates know about our job openings.

But this time we're also going to try an experiment. Although Sunlight has always been committed to being an equitable and inclusive employer, there is good research indicating that applicants' identity can affect screening decisions, perhaps even in ways that the screener doesn't realize. So we are asking that applicants for this position keep their names and contact information separate from their cover letters and resumes through the use of this handy web form.

This is an experiment, and we know it probably won't work perfectly. Obviously we need to know where you've worked and what your code looks like, and, in some cases — hopefully not that many — this might leak information about who you are. And once we get to phone and in-person interviews, we'll inevitably develop a more specific sense of a candidate's identity. But we think this is worth a try, and we ask that applicants make a good faith effort to anonymize their resumes and cover letters.

Beyond that: We need your help! If you know a talented engineer who wants to make their country better, please make sure they know about this job. Sunlight is a great place to work. We're all pretty excited to meet the next Kaitlin.

Newsletter! Jobs!

Newsletter sidebarData Community DC is thrilled to announce three new things!

  1. We've got a newsletter! Or, rather, a new newsletter! For quite a while we've had an automated daily newsletter that you could subscribe to, but it just sent you any new blog content. Our new newsletter is weekly, will be edited/curated, and contains highlight's of the last week on the blog, next week in events, and more. You should definitely subscribe!
  2. We've got job listings! Nothing makes us happier then hearing about people making career connections through DC2's events. And now we've got a new way to actively help you find an amazing new job, or an amazing new employee. Our job ads will be published in the newsletter, and they'll be short, targeted, and to the point. So subscribe to the newsletter now! If you've got a position you're looking to fill, posting in DC2's newsletter is your best option for reaching data/statistical/analytics professionals in the DC area. You should definitely submit an ad! Free for nonprofits, government, and sponsors; super-cheap for everyone else.
  3. We're hiring! DC2 is a volunteer-run organization. But the amazing support from our sponsors, as well as revenue from workshops and advertising, means that we've decided to post two roles. First, we want to hire someone for five hours a week to help produce the newsletter, manage our job ads, etc. Second, we've got a few graphic/web design needs, and want to find a freelance designer who can help us on a project basis. Interested? More details are posted here.

As always, DC2 mission is to promote, education, and network data professionals in the region. Got an idea for something we should be doing? Get Involved!

SynGlyphX: Hello and Thank You DC2!

The following is a sponsored post brought to you by one of the supporters of two of Data Community's five meetups.

Hello and Thank You DC2!

This week was my, and my company’s, introduction to Data Community DC (DC2).  We could not have asked for a more welcoming reception.  We attended and sponsored both Tuesday’s DVDC event on Data Journalism and Thursday’s DSDC event on GeoSpatial Data Analysis.  They were both pretty exciting, and timely, events for us.

SynglyphyxAs I mentioned, I’m new to DC2 and new to the “data as a science” community.  Don’t get me wrong, while I’m new to DC2 I’ve been awash in data my entire career.  I started as a young consultant reconciling discrepancies in the databases of a very early Client-Server implementation.  Basically, I had to make sure that all the big department store orders on the server were in sync with the home delivery client application.  A lot of manual reconciling that ultimately led to me programming code to semi-automatically reconcile the two databases.  Eventually (I think) they solved the technical issues that led the Client-Server databases being out of sync.

Synglyphyx2More recently, I was working for a company with a growing professional services organization.  The company typically hired new employees after a contract was signed; but the new professional services work involved short project durations.  If we waited to hire, the project would be over before someone started.  We developed a probability adjusted / portfolio analysis approach to compare supply of available resources (which is always changing as people finish projects, get extended, leave the organization) vs. demand (which is always changing as well), that enabled us to determine a range of positions and skillsets to hire for in a defined timeframe.

In both instances, it was data science that drove effective decision making.  Sure, you can apply some “gut” to any decision, but having some data science behind you makes the case much stronger.

So, I was fascinated to listen to the journalists discuss how they are applying data analysis to help:  1) support existing story lines; and 2) develop new story lines.  Nathan’s presentation on analyzing AIS data was interesting (and a bit timely as we had just gotten a verbal win for a client on doing similar type work, similar, but not exactly the same).

I know the power of data to solve complex business, operational, and other problems.  With our new company, SynGlyphX, we are focused on helping people both visualize and interact with their data.  We live in a world with sight and three dimensions.  We believe that by visualizing the data (unstructured, filtered, analyzed, any kind of data), we can help people leverage the power of the brain to identify patters, spot trends, and detect anomalies.  We joined DC2 to get to know folks in the community, generate some awareness for our company, and to get your feedback on what we are doing.  Thank you all for welcoming us and our company, SynGlyphX, to the community.  We appreciated everyone’s interest in the demonstrations of our interactive visualization technology.  Our website traffic was up significantly last week, so I am hoping this is a sign that you were interested in learning more about us.  Additionally, I have heard from a number of you since the events, and welcome hearing from more.

Here’s my call to action, I encourage you to tweet us your answer to the following question:  “Why do you find it helpful to visually interact with your data?”

See you at upcoming events.

Mark Sloan

About the Author:

As CEO of SynGlyphX, Mark brings over two decades of experience.  Mark began his career at Accenture, co-founded the global consulting firm RTM Consulting, and served as Vice President and General Manager of Convergys’ Consulting and Professional Services Group.

Mark has a M.B.A. from The Wharton School of the University of Pennsylvania, and a B.S. in Civil Engineering from the University of Notre Dame. He is a frequent speaker at industry events and has served as an Advisory Board Member for the Technology Professional Services Association (now Technology Services Industry Association (TSIA)).

The Sunlight Foundation is looking for an Enthusiastic Software Developer

This guest post is a job listing reposted from the Sunlight Foundation. 

The Sunlight Foundation uses cutting-edge technology and ideas to make government more open and transparent. We're a non-partisan non-profit organization, founded in 2006, with more than 50 employees, including journalists, policy advocates and software developers.

Software Developer

The Sunlight Foundation is looking for an enthusiastic software developer to join our ranks in Washington, DC and expand the breadth and sophistication of what we're doing with government data. This is a new position.

We collect huge amounts of information throughout the day from all over Congress, the U.S. executive branch, and state and municipal governments. We use this information to build powerful, impactful websites (such as Open States and Scout; mobile applications (such as our Congress apps for Android and iOS); and APIs (like these). Along the way, we make heavy use of GitHub to work with other groups and developers to build an ecosystem of tools and datasets for the entire open government community (you can see some examples at and

We want to do more of all of this. If you take this position, you'll be asked to:

  • Find and incorporate new sources of useful data into our APIs and applications.
  • Create new open source tools that solve real problems for Sunlight, our users and others in the open government community.
  • Research and develop cutting edge ways of using our data to create innovative features and solve new kinds of problems.
  • Notice what we're not doing but should be, and do it.

This position will be part of a small team that focuses on many of the projects listed above. There will be plenty of opportunities to work with other teams in our technology department, as well as Sunlight's journalists and policy staff.

You'll also be asked to use a wide variety of programming languages and technologies.

Some technologies we use at Sunlight:

  • Web, system, and tool development with RubyPython, and Node.
  • Front-end and data visualization in JavaScript (and especially D3).
  • Both SQL and NoSQL, with PostgreSQL and MongoDB.
  • Searching lots of text using Elasticsearch and language analysis.
  • Native app development on Android (Java) and iOS (Objective-C).

You don't need to know all of these, but you should know a couple of them, and be able to learn some others.

Sunlight works in both cyberspace and the physical world, so in addition to writing code, it would be an extra bonus if you enjoy writing about your work, public speaking on Sunlight's behalf or meeting with people both inside and outside of government.

To apply, send an email to with your name and "Software Developer" in the subject line. Include your cover letter in the body and include a link to your GitHub account or other open-source work. Attach or link to a resume.

We will confirm receipt of all applications made to No phone calls, please. Recruiters: principals only.

Principal applicants only. Contact us by email only, all applicants will be contacted.

Want to Learn Data Science? Get a Personal Tutor from SageBourse, a Hot New Startup in DC

SageBourseSageBourse is a tutoring marketplace for data science and programming. It's essentially a way for people who want to enhance their data science and programming skills to get personalized instruction from others in the community that are knowledgeable about those subjects. This can be either in person or online. The process is pretty simple. Tutors sign up and choose which subjects they know well enough to teach. When someone requests a lesson in a subject, the tutors that can teach that subject get notified and have the opportunity to bid on the lesson. Once the student chooses which bid they'd like to accept, they are connected with the tutor so they can coordinate a time that works best for both of them. When the lesson is over, SageBourse takes care of collecting payment from the student and paying the tutor.

This provides those that want to learn data science and programming an easy, affordable, and efficient way to do that. It also provides those that can teach these subjects the ability to leverage the knowledge they have to make a some extra money.

According to the Founder, DC2's very own Tony Ojeda:

Tony Ojeda_smallThere's an increasing amount of data being made available every single day.  I strongly believe that the more people we arm with the skills necessary to turn that data into information, and then do something useful with that information, the better off we will be.  Organizations are becoming more data-driven and the jobs of tomorrow are going to reflect that.  Technology is advancing and if your skills aren't advancing with it, you risk getting left behind.  I created SageBourse to help give people the ability to not only catch up with technology, but get ahead of it.

Selling Data Science

Data Science is said to include statisticians, mathematicians, machine learning experts, algorithm experts, visualization ninjas, etc., and while these objective theories may be useful in recognizing necessary skills, selling our ideas is about execution.  Ironically there are plenty of sales theories and guidelines, such as SPIN selling, the iconic ABC scene from boiler room, or my personal favorite from Glengarry Glenross, that tell us what we should be doing, what questions we should be asking, how a sale should progress, and of course how to close, but none of these address the thoughts we may be wrestling with as we navigate conversations.  We don't necessarily mean to complicate things, we just become accustomed to working with other data science types, but we still must reconcile how we communicate with our peers versus people in other walks of life who are often geniuses in their own right.

We love to "Geek Out", we love exploring the root of ideas and discovering what's possible, but now we want to show people what we've discovered, what we've built, and just how useful it is.  Who should we start with?  How do we choose our network?  What events should we attend?  How do we balance business and professional relationships?  Should I continue to wear a suit?  Are flip-flops too casual?  Are startup t-shirts a uniform?  When is it appropriate to talk business?  How can I summarize my latest project?  Is that joke Ok in this context?  What is "lip service"?  What is a "slow no"?  Does being "partnered" on a project eventually lead to paying contracts?  What should I blog about?  How detailed should my proposal be?  What can I offer that has meaning to those around me?  Can we begin with something simple, or do we have to map out a complete long term solution?  Can I get along professionally with this person/team on a long term project?  Can I do everything that's being asked of me or should I pull a team together?  Do I have the proper legal infrastructure in place to form a team?  What is appropriate "in kind" support?  Is it clear what I'm offering?

The one consistent element is people: who would we like to work with and how.  This post kicks off a new series that explores these issues and helps us balance between geeking out and selling the results, between creating and sharing.

The Top 5 Questions A Data Scientist Should Ask During a Job Interview

The data science job market is hot and an incredible number of companies, large and small, are advertising a desperate need for talent.
Before jumping on the first 6-figure offer you get, it would be wise to ask the penetrating questions below to make sure that the seemingly golden opportunity in front of you isn't actually pyrite.

1) Do they have data?

You might get a good laugh at this one and probably assume that this company interviewing you must have data as they are interviewing you (a data scientist). However, you know what they say about ass-u-ming, right?

If the company tells you that the data is coming (similar to the "check is in the mail"), start asking a lot more questions. Ask if the needed data sharing agreements have been signed and even ask to see them. If not, ask what the backup plan is for if (or when) the data does not arrive. Trust me, it always takes longer than everyone thinks.

To be an entrepreneur means to be an optimist at some level because otherwise no one would do something with such a low probability of success. Thus, it is pretty easy for an entrepreneur to assume that getting data will not be that hard. It will only be after months of stalled negotiations and several failures that they will give up on getting the data or, in startup parlance, pivot. In the meantime, you best figure out some other ways of being useful and creating value for your new organization.

2) Who will you report to and what is her or his background?

So, really what you are asking is: does the person who will claim me as a minion actually have experience with data and do they understand the amount of time that wrangling data can take?

If you are reporting to an Management/Executive type, this question is all important and your very survival likely depends on your answer.

First, go read the Gervais Principle at ribbonfarm. From my experience, the ideas aren't too far off of the mark.

Second, many data-related tasks are conceptually trivial. However, these tasks can take an amount of time seemingly inversely proportional to their simplicity. Or, even worse, something that is conceptually very simple may be mathematically or statistically very challenging or require many difficult and time-consuming steps. Something like count the number of tweets for or against a particular topic is trivial for people but less so for algorithms.

Further, as everyone knows, data wrangling on any project can consume 80% or more of the total project time and, unless that manager has worked with data, she or he may not understand this reality. The rule of thumb to never forget is that if someone does not understand something, that person will almost always under appreciate it. I swear there must be a class in American MBA programs that teaches if you don't understand something it must be simple and only take five minutes.

If you are reporting to a CTO-type, the situation may seem better but it actually might be worse. Software engineering and development do not equal data science. Technical experience, most of the time, does not equal data experience. Having gone through a few semesters of calculus does not a statistics background make. Hopefully, I have made my point. There is a reason we call the fields software **engineering** (nice and predictable) and data **science** (conducting experiments to test hypotheses). However, many technically-oriented people may believe they know more than they actually do.

Short version for #2 is that time expectations are important to flesh out up front and are highly dependent on your boss' background.

Third, your communications strategy will change radically depending on your boss' background. Do they want the sordid details of how you worked through the data or do they just want the bottom line impact?

3) How will my progress and/or performance be measured?

Knowing how to succeed in your new workplace is pretty important and the expectations surrounding data science are stratospheric at the moment. Keep your eyes peeled if there is a good quick win available for you to demonstrate your value (and this is a question that I would directly ask).

The giant red flag here is if you will be included in an "agile" software process with data-work shoehorned into short-term sprints along with the engineering or development team. Data Science is science and many tasks will often have you dealing with the dreaded unknown unknown. In other words, you are exploring terra incognita, a process that is unpredictable at best. Managing data scientists is very different than managing software engineers.

4) How many other data scientists/practitioners will you be working with and are in the company overall?

What you are trying to understand here is how data-driven (versus ego-driven) the company that you are thinking of joining is.

If the company has existed for more than a few years and has few data science or analyst types, it is probably ego driven. Put another way, decisions are made by the HiPPOs (the HIghest Paid Person's Opinions). If your data analyses are going to be used for internal decision making, this possibly puts you, the new hire, directly against the HiPPOs. Guess who will win that fight?  If you are going into this position, make sure you will be arming the HiPPO with knowledge as opposed to fighting directly against other HiPPOs.

5) Has anyone ever run analyses on the company's data?

This one is critical if you will be doing any type of retrospective analyses based on previously collected data. If you simply ask the company if they have ever looked at their data, the answer is often yes regardless of whether or not they have as most companies don't want to admit that they haven't. Instead, ask what types of analyses the company has done on its data, did the examination cover all of the companies data, and ask who (being careful to inquire about this person's background and credentials) did the work.

The reason this line of questioning is so important is that the first time you plumb the depths of a company's database, you are likely to dig up some skeletons. And by likely I really mean certainly. In fact, going through historically collected data is much like an archeological excavation. As you go further back into the database, you go through deeper layers of the history of the organization and will learn much. You might find out when they changed contractors or when they decided to stop collecting a particular field that you just happen to need. You might see when the servers went down for a day or when a particularly well hidden bug prevented database writes for a few weeks.  The important point here is that you might uncover issues that some people still present in the company would prefer not to be unearthed. My simple advice, tread lightly.

Small DoD Engineering Company Offers Silicon Valley Experience in Nation's Capital (Sponsored Blog)

The following is a sponsored blog post from a local company. horizontal white on medium blue in CMYKWe’re a small DoD engineering company, and we are looking for a cloud software engineer with an entrepreneurial spirit who would enjoy a Silicon Valley experience right here in DC.  Join the team with a kick-off innovation workshop led by Frog Design and work toward demonstrations that will be featured in tech magazines. If you enjoy hands on work, have the maturity to take a leadership role on tasks, enjoy working in a mixed community of researchers and developers, and hold a DoD clearance, please check out our job ad here: