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Data Scientist in a Fast-Paced & Collaborative Environment


Name: Jordan Sorokin (he/him)

PhD: Neuroscience, Stanford, 2019



What was your main area of research?

I studied the neural dynamics underlying seizure initiation & termination using rodent models of absence epilepsy. I used in vivo recordings paired with optogenetics and real-time monitoring systems to detect seizure initiation & stimulate a specific region of the brain to stop the seizures. I utilized multi-electrode arrays to dig into pre-seizure dynamics to evaluate whether seizure prevention vs. termination is possible.



What is your current job?

I am a Staff Data Scientist at Recursion and located in Fort Collins, Colorado.


Having both computational and wet-lab experience, I have a diverse role at Recursion. A typical week might include: focusing on updating some computational workflow, developing new methods for high-dimensional datasets such as RNAseq, working with biologists to design experiments, analyzing some dataset to confirm or reject a hypothesis around a candidate molecule for a disease program, and/or prepping/giving a talk on some findings.


There is always something new to learn / a new project to dive into. I knew by year 4 of my PhD that I don't have the personality type required to stay focused on a project/question for years. Working in a fast-paced & collaborative setting such as Recursion, where there are experts across a wide variety of domains to constantly learn from and work with, suits my working style perfectly.



How did you find this position? What were the career steps you took to get to where you are now? 

I started doing some research into machine-learning/data-science enabled biotech towards the end of my PhD. I landed on this role with a combination of networking + persistence.


PhD ➡️ (small startup) Computational Neuroscientist ➡️ Sr. Machine Learning Scientist ➡️ (Recursion) Sr. Computational Biologist ➡️ Staff Data Scientist



Why did you decide to not pursue a career in academia? Was this a difficult decision or one you felt came easily?

I had mixed emotions (and to be honest still do). I love the idealism of academia, but dislike the actual working environment. I found the most joy in the lab when collaborating with others vs. driving my own projects forward. This was a clear signal that professorship was likely not the right path for me. After a year or so of debating, I decided to pursue something new, and I'm happy I did.



What are three pieces of advice you have for someone getting their PhD and looking to pursue a career outside of academia?

  1. Seek mentorship outside of your immediate circle. There is bias (whether admittedly or not) within your lab/official mentors to promote academia. Even just reaching out to other professors that have fewer stakes in your career trajectory can be very helpful.

  2. It's never too early — nor too late — to diversify your skillset. Take an engineering, business, software, or data science course or two. Use your university to your benefit! Diversity of skillsets is one of the things I look for when interviewing candidates.

  3. Don't let imposter syndrome prevent you from pursuing roles outside of your immediate area of expertise. Some of the best candidates come in with very different ways of thinking. It's more important to be a critical thinker, fast learner, and collaborative team-member above all else.

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