WiMLDS Member Spotlight: Ramya Narayanaswamy

WiMLDS Member Spotlight is a place where we celebrate the voices of our diverse community of amazing women, from seasoned experts to young professionals and recent graduates.

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Spotlight on: Ramya Narayanaswamy

Machine Learning Engineer, Bay Area
Pronouns: she, her, hers

What do you do for a living? How do you explain your job to people outside of your field? I am a Machine Learning Engineer. I bridge the gap between research/ideas and product via engineering.

How did you get into DS & ML? What was your learning process? I did it in a formal way: went to a graduate school and took ML-related courses initially. Learning is a continuous process. After that, kept reading papers, blogs and took Coursera courses.

How did you get your first job in DS & ML? I used LinkedIn extensively. I did set job alerts, and found a position. Took me 3 months, ~30 applications, and 4 failed interviews before I landed a job.

What does your workday look like? What do you spend the most time on in your day? My workday involves Python coding for creating and improving feature pipelines, training and metric pipelines, for various deep learning models. Apart from that, I create necessary tools or scripts for deploying and monitoring models.

What is your DS/ML toolkit? Tensorflow, Python, Spark.

What are your pet peeves when it comes to DS & ML? When I try to explain in plain English to a non-technical person, the reason behind the predictions of a Deep Learning model.

What they don’t teach you at school: what surprised you the most in the first few years of your career? Most of the time (about 80 percent) is spent in understanding data, feature engineering and analyzing the outputs of the model. Schools teach just ML or DL algorithms in toy datasets. Scalability issues are also not taught.

If you could help all data scientists to magically power-level one skill, what would it be? Spark.

What books and media outlets would you recommend to an aspiring data scientist? TheSequence newsletter, Towards Data Science Medium channel, Arxiv Sanity Preserver plugin for keeping tabs on latest or popular papers.

How can women, and folks in gender minorities, better support each other in DS? Being a champion for each other.

What types of people do you enjoy collaborating with? People who can give and take feedback, people who see learning as a continuous process.

Who do you admire in the field? Cassie Kozyrkov and Allie Miller.

How do you find mentors? How do you ask for mentorship? Understand where you want to be in a few years: Data Science, ML engineering, ML infrastructure, etc. The first option is to request senior folks/experts in your current company if they can mentor you after you have shown dedication and curiosity.

The next option is through any community (like WiMLDS) and/or ping experts (aka cold call) in LinkedIn, share your projects and interests, and request for mentoring.

What do you do to recharge after an intense workday? Yoga.

What are the small things that bring you joy? Reading, and eating a good meal.

What is the best way to get connected with you?
Via LinkedIn.

To hear about more women who share their innovations and skills in Machine Learning and Data Science, join our group on Meetup, and follow WiMLDS on Twitter and LinkedIn.

Prepared by: Elena Semeyko