the cognistx blog

Chat with Cognistx Data Scientist Roshan Bhave During Covid-19

April 23, 2020
Holly Weaver

In this conversation between Holly Weaver and Roshan Bhave, a Data Scientist explains how Artificial Intelligence affects all of us and how to adapt in the new norm of Covid-19.

Name:  Roshan Bhave
Age:  25
Location:  Pittsburgh, PA
Hometown:  Charlotte, NC
Position:  Data Scientist at Cognistx
Alma Mater:  Georgia Tech

Holly:  First off can you tell us a little bit about yourself and what you do?

Roshan:  My name is Roshan Bhave.  I am a Data Scientist at Cognistx and what I do is brainstorm on solving various business problems and translating solutions into usable algorithms.  So, along that route, I’m involved in a lot of data science modalities, which involves data preprocessing, data ingesting and cleaning, feature engineering and modeling testing.

Becoming a Data Scientist at Cognistx is a huge accomplishment.  What has your experience been like getting to where you are today?

It’s been a great learning experience.  Initially, I had come in understanding basic Python structures and formatting, and from there, as I was working with various clients, I understood the business aspects of being a Data Scientist, in terms of understanding the problem, understanding the flow of variables and translating that understanding into viable code.  I’ve understood what specific topics to research in my field, which pertains to a particular problem at hand for a client and it’s given me a lot of business skills in terms of interacting with the client, understanding what the client wants and basically letting them know in layman terms how our solution will help them.

What challenges did you face becoming a Data Scientist?

So, some of the challenges I faced were getting a strong understanding of what models to use for specific problems. That came with a bit of experience and different projects, as well as interacting with some of the Senior Data Scientist members and learning from them, such as Anna Belova and Eric Nyberg. Another challenge was setting proper timelines for given data science tasks.  That came with experience as well by working on different projects and understanding an accurate estimate of how long a given project would take.

What’s the best piece of advice you can give our readers who also have big dreams and want practical tips on how to achieve them?

I would say, be cognizant of what’s going on in the data science industry.  Be up to speed on some of the topics of data science - some of the newest and freshest algorithms out there - as well as the upcoming research that’s going on.  I would also suggest watching videos and TED talks which highlight why data science and AI is going to be significant in the coming years, and along with that any videos or tutorials which help the reader understand how to deploy any data science technique in Python or R or any given programming language.

It’s not everyday that you get to work on something as big as AI.  What was your initial reaction?

I was definitely excited... a little bit intimidated too, but more so excited to get an opportunity to work with probably the most state of the art technology today.  I was ready to research for sure.  That was one thing I was excited about.  Researching and seeing the different types of use cases in terms of AI technology which I could implement in given projects.  So, I would say the research aspect and ability to creatively express how I would solve a problem in code is what made me the most excited.  The intimidating factor was whether or not I could get the work done in a given time and another intimidating factor was the unknown amount of work that would entail in a given project when I first started.

What about Cognistx and the brand made you want to work here?

As a startup company, Cognistx does not have too many employees, and that is a very good opportunity for an upcoming Data Scientist because they have their own responsibility within a given project, so they have an opportunity to shine and to lead a project.  Along with Data Scientists, we’re also becoming leaders and understanding how to direct a project and how to lead from a Data Science role and interact with clients.  Along with being a Data Scientist, I feel like I’ve also become a leader, and that is a very attractive trait of being a Data Scientist at Cognistx.

How do you use AI in your own life?

I probably use AI myself to set a lot of daily tasks such as scheduling, as well as entertainment.   Specific music which uses AI algorithms to give me the best music that I’d like to listen to based on my historic playlists.  Along with that, I would say that AI is also used in a lot of the technological processes that I use daily, whether it be ordering food or listening to music or scheduling a ride from Uber or getting around places.  Those all involve a level of AI for sure.  I would say a lot of modern technology that we are reliant on uses a form of AI with varying complexity levels.  I would say mostly everybody these days uses AI whether they know it or not.

So, what are you listening to right now?

Right now I am currently listening to... I was actually listening to The Weeknd and Daft Punk recently.  I felt called for the song, I Feel It Coming. It’s a very melodic song and I have found a lot of similar songs through the algorithm in Spotify, which highlights similar songs in terms of the genre as well as the style of music.  So, that AI aspect has allowed me to find similar songs to I Feel It Coming.

There is a discovery aspect to AI.  How do you think our algorithms compare to an app like Spotify?

Our algorithms can be a bit more complex since a lot of what we do is in the Natural Language Processing field.  For example, we have worked with a cybersecurity company where we’ve highlighted a lot of unknowns in the deep dark web to the given client.  So in that respect our algorithms are in a different field and are definitely showing a lot of valuable insights from a cybersecurity perspective and I would say our algorithms as well are highlighting statistical anomalies or outliers from a Data Quality Engine perspective, which gives valuable insights to the user on the different statistical outliers that they were unaware about.

It’s been two years since you started working with Cognistx.  What does this anniversary mean to you?

I would say this anniversary means a lot to me in terms of my growth as a Data Scientist, as well as the growth of the company too.  Because I've been here for two years, I’ve seen challenges that Cognistx has faced and I’ve seen us overcome a lot of these challenges as well.  I would say throughout my two years I’ve begun to realize how strong of a team Cognistx has, and it’s also made me mature as a young professional in terms of understanding the different roles required in a company to succeed.  So, it’s definitely given me insight on what a company needs to be successful and who a company needs to be successful.  It’s given me a lot of insight as a Data Scientist on how I can improve my skills in terms of coding for sure.  I’ve also gained a lot of engineering skills through working with Software Engineers.  It’s also given me a strong understanding on what a client wants and how to convey a proper solution as a Data Scientist to those clients.  So, this anniversary is very significant because it’s definitely given me a more holistic picture of how the AI industry is thriving in the current market and how to progress to be a successful AI company.

What do you count as your biggest accomplishment since graduating from Georgia Tech?

I would say my biggest accomplishment is definitely getting a lot of great work done at Cognistx, whether it be from Armada or from Kroll.  I would say working with Kroll was a big highlight for me because it was working on a lot of deep dark web data and I felt like I was on the front line with the Kroll team, as well as Eric Nyberg himself.  We had discovered a lot of valuable insights in the deep dark web in terms of understanding what potential indicators could be for breeches as well as the different types of files seen on the deep dark web that Kroll themselves were unaware about.  So, I would say that working on significant projects that led to results that were unprecedented.  My first year at Cognistx was probably my biggest accomplishment because I proved not only to the company, but to myself that I could thrive as a Data Scientist.

How has the Coronavirus epidemic affected you personally?

Personally, I am not too affected because I’m slightly introverted, so staying at home is not something I am not used to.  In terms of work, it has actually made me more comfortable working because I am in a very stagnant space.  I am getting my work done in, I guess, a more controlled environment.  Along with that, I feel like it’s given me an opportunity to think a little differently on various problems.  I would say the only thing that’s really getting impacted are my workouts.  I can no longer go to the gym, so I am trying to adjust those workouts effectively.  I would say that’s the biggest adjustment.  Work has not really been too impacted, but I feel like I am altering my perspective a little bit on how I’m approaching data science work just due to a change in environment.

How have your workouts changed since you’ve had to stay home?

I’m doing a lot more body weight type workouts.  I’m also doing a lot more yoga and stretching type of workouts as well as any cardio-based workout I can do in the home, whether it be mountain climbers or burpees.  It’s definitely eliminated lifting for me, so my spine gets a rest as well as my joints, and it has given me an opportunity to be more flexible and more grounded in terms of body weight strength.

Are there any workouts online that you would suggest?

I would suggest a lot of workouts from Athlean-X.  He is Jeff Cavaliere.  He has trained a couple of professional sports teams.  He is a great workout instructor who gives a lot of example workouts on what to do.  He has a lot of home workouts on YouTube.  The reason I like him is because he uses scientific facts and facts about anatomy to back up why his workout is efficient, why it would not cause any injury, how to avoid injury and how to get stronger.  So, I would definitely suggest Athlean-X for anybody who is trying to be smart about their workout and trying to be creative with their workout.

Where do you see AI going in the future and how has AI been affected by the current events?

I would say in the future I do see AI becoming powerful in terms of the amount of data that we have currently.  I do think that AI in the future would be able to replicate a lot of human intelligence and in some cases I feel like it will exceed human intelligence in terms of understanding various trends in data.  I would say over time, as AI improves, the amount of data we have increases as well, and of course the more data there is the more powerful and intelligent AI will become.  So, I do foresee a big explosion of intelligence from AI in the coming years.  I do feel that we are on the brink of a rapid technological expansion.

Finally, is there a charity that you’re passionate about?

I am passionate about the Humane Society and helping out with animals as well as St. Jude’s Hospital, helping children who are suffering from terminal illness.  So, I would say the National Humane Society, as well as St. Jude’s Hospital are both charities I’m passionate about helping for sure.

Roshan, thank you for your time today and I appreciate all of these answers.

Of course, Holly, thanks for interviewing me.  I really appreciate it.

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