Meet A Data Scientist: Dr. April Harry
We are excited to present the first article in our new series “Meet A Data Scientist”! We are going to chat with some amazing women in data science, in the Puget Sound area, to learn about their journey into the field, their incredible accomplishments, and some meaty challenges that they faced along the way. This lies at the heart of the mission of Data Circles of inspiring women in the field by showcasing role models.
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Dr. April Harry, Data Scientist at Rover.com in Seattle, describes her journey into data science after finishing her doctoral degree in statistics, and shares some tips about doing well in the field.
Like many transplants from academia in data science, April found her way into data science through the Insight Data Science Fellows (or Insight) program. She had a successful run at graduate school and on graduation, in December 2017, she became the first African American woman to earn a doctorate in Statistics from Purdue. As her program came to an end, she was confident that she wanted to move out of academia. April was looking forward to moving into industrial positions where she could strike a good balance between research and applied projects. At this juncture, her friend, who was a program director at Insight, convinced her to give the field of data science and the program a chance. Following her friend’s advice, April applied and was successfully accepted into the January 2018 cohort of the program in Seattle.
“When she was moving from academia, people cautioned April about the money-driven culture in the industry, but she was relieved to find that this was only a misconception. ”
April speaks fondly of the Insight program which was able to provide her with the right skills for the industry. Before starting at Insight, she had tested the waters by applying to a few data science positions. However, she quickly realized her experience in R and statistical methodologies obtained from graduate school was not enough to be competitive in the data science job market. She needed to learn Python and other data science algorithms. Fortunately, Insight was able to provide both theoretical knowledge and experience with their project-based curriculum. She amassed relevant skills by writing her own web-scrapers, cleaning data, building models, and learning Python on the fly. Additionally, she also practiced interviewing skills, like explaining algorithms on the blackboard, at the program.
“April notes that practicing the non-technical parts of the interview was really important to her success. These questions typically start with “Tell me about a time when …”, which candidates often take lightly.”
After months of hard work at Insight and a successful interview season, April decided to start her data science career at Realself.com. She was delighted about her first job as a data scientist. She spoke fondly of the smart, motivated people on her team. After a year-long tenure at Realself.com, April moved on to Rover.com, where she is currently employed. Being a dog-owner herself, April is motivated and excited by the mission of Rover.com. In fact, as a potential customer of the company, she is able to think like the customer, and make better models for the customer.
In her two years as a data scientist, April has already contributed towards many exciting projects. Previously, at RealSelf.com, she was able to boost the performance of an email marketing campaign by 20% by improving the data pipeline. She was incredibly excited about the large and immediate impact of her work on the business. Now, at Rover.com, she is helping improve the search algorithm that allows pet owners to search for the right care for their pet. She develops models that surface the pet sitters who are the best fit for a pet owner’s need on the website and app. What is most exciting to her is that she is able to develop features for these models using her personal pet-care experiences.
In her time in the industry years, April has come to realize that communication is the most important tool in a data scientist’s toolbox; more powerful than the latest algorithms. She recalls spending considerable time conversing with stakeholders and getting buy-ins for various projects. This contrasts sharply with her past life in academia which largely emphasized technical know-how.
“For candidates looking to sharpen their communication skills, April advises them to practice drawing pictures to explain algorithms. This will not only display mastery in communication and visualization, but also technical prowess.”
In addition to her job, April makes the time to give back to the Insight community by mentoring new students. Since she found a supportive community at Insight, she wishes to provide the same for others. April also enjoyed the community of data scientists at both Realself.com and Rover.com. They were both women-majority data science teams, a rarity in the technology industry. It is the strong community support at Insight and her workplaces that keeps April motivated to work and grow in the field of data science.