Data science means different things to different people. The field is still new (as recently as 2011, when I left graduate school, most companies in San Francisco were still only hiring “data analysts”), and there is an ongoing debate about what separates data analysts from data scientists and data scientists from data engineers.
Meanwhile, I’ve noticed that different cities tend to have different hiring cultures and requirements for data scientists, even if the work they do ends up being pretty much the same. In most of the San Francisco startups I’ve worked with, the requirements are on the looser side: if you are a scrappy problem-solver with a strong numerical intuition who can write Python, you’re basically hirable. Compare that to Seattle, where a program manager for Insight Data Science told me they have to train their Fellows to pass a software engineering interview if they want them to get hired.
Complicating this issue is the reality that many companies put out job requisitions for a “Data Scientist” when they are really looking to hire a Data Analyst or a Data Engineer. If you want to do data science, you’ll either get prematurely screened out of these jobs because your skills don’t match what they’re actually looking for, or you’ll get halfway through the interview process before you realize that this isn’t actually the job you want.
So how can you ensure you’re applying to jobs that actually fit with your skillset and are of interest? You need to ensure you’re targeting people who have the same understanding of data science that you do.
The Insight Hack
Insight Data Science is training program for PhDs transitioning into data science. I’ve worked with them on and off for the last five years, and they consistently produce a very high level of data science talent. The Insight team’s philosophy on data science is similar to mine: they put a high premium on numerical intuition and product sense. Each Insight Fellow builds a unique data-powered web product during their training, which emphasizes that data scientists should focus their efforts on solving real-world business problems (even as they put their research skills to good use). As a result, Insight Fellows tend to have a sophisticated understanding of what makes a good data scientist, and what makes a data scientist different from a software engineer.
So if you want to find a group of people who are doing the kind of data science you want to be doing, you should filter for Insight Fellows.
Filtering for Insight Fellows means filtering for the best companies
The Insight hack operates under this hypothesis: In the set of all companies hiring data scientists, the subset of companies that have hired Insight Fellows will be a higher quality subset for you to target as you search for jobs. The hunch that these companies are of higher quality is grounded in three contributing factors:
- Insight Fellows are good data scientists, so the companies they choose to work at will tend to be good (i.e., have funding, have interesting problems, have enough data to work with, have a good leadership team, etc.).
- The Insight program itself tends to filter for the best companies when they are placing Fellows in their first jobs. Part of that filtering process involves making sure that the companies they work with have a good understanding of what data science is: i.e., the company is not hiring a data scientist to run reports for the product team, and the company understands the difference between a data scientist and a software engineer.
- A company that has hired an Insight Fellow is a company that already knows how to work with data scientists. They are less likely to ask their data scientists to act purely like software engineers or BI analysts. These are the companies that understand how data science should work at their company—either because they understood that before they hired the Insight Fellow, or because the Insight Fellow has subsequently educated them.
Use LinkedIn to search for past Insight Fellows
You can use LinkedIn to search for people who have done the Insight Data Science Fellowship program sometime in the past. Those people are all going to be Data Scientists at companies that value the kind of data science Insight trains their fellows to do. Many of them will by this point be hiring managers, since Insight Fellows tend to rise through the ranks quickly. Once you’ve identified which companies in your area have hired Insight Fellows, you can target those companies with your cold email.
You’ll also want to find former Insight Fellows in your city of choice, which you can filter for on LinkedIn.
First, go to your homepage and search for “insight data science.” (Just type in the phrase and hit “enter,” rather than choosing the company from the drop-down menu.)
On the search results page, click “All Filters.”
Enter your location (or locations) of choice. Then, under “Past companies,” check the box for “Insight Data Science.”
Click “Apply” to apply the filters.
This search will return a list of past Insight Fellows who are currently based in your location(s) of choice. Scrolling through the list, you can see which companies they work at and add them to your list of companies to research and potentially reach out to via cold email.
One caveat: Insight offers fellowship programs in Data Engineering, Data Product Management, AI, DevOps, Security, and other fields in addition to Data Science. So you may find your search turns up former Fellows who are not in data science. If that’s an issue, you can further filter your search by adding a keyword like “data,” “data science,” or “data scientist” to your search.
You still want to email the hiring manager
While all the Insight Data Science Fellows are great data scientists, they won’t always be the right people for you to target with your cold email. The Insight hack is a method for finding the right *companies* to apply to. You still need to do your research in order to…
- Determine that there is a job req out at the company that you think you’d be a fit for.
- Figure out who is the hiring manager that you should email.
Remember, you want to target the decision maker here, as I explained in my earlier post on finding the right cold email contact. You want to find the hiring manager and contact them—which will not necessarily mean you’re contacting the former Insight Fellow you found in your search.
However, you may luck out and find that the Insight Fellows you discover in your search are, in fact, the hiring managers you want to reach out to. For example, my first search with these filters turned up a profile that included this solicitation:
You can also combine your Insight Fellows search with my “I’m hiring” job search hack to filter down to a select pool of hiring managers.
Let me know how it works!
Insight’s fellowship programs are currently based in Silicon Valley, New York, Boston, Toronto, Seattle, and Los Angeles, so this hack will work best if you’re searching for a job in one of those cities. However, they do have remote fellowships, and people can always move after they finish the program, so even if you’re not based in one of those cities, the hack is still worth a try. Comment below and let me know how it worked for you!
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