When Dionna Jacobson joined Nayya as a senior data scientist in 2022, she knew she’d have a lot to learn.
“My prior work experience was focused on model development and not deployment, and I needed to fill that skills gap,” she told Built In New York. “I enrolled in a course to learn about machine learning operations including modules like model management and delivery, observability, data version control, container orchestration and kubernetes.”
Jacobson isn’t alone in her desire to level up her skills and stay at the top of her game — as data science continues to advance and change, many professionals are looking for companies that will help them develop and build their careers.
At Nayya, she has found that growth and support. An investment in learning is paired with a commitment to offering fresh challenges and cutting-edge projects to give team members room to advance.
Built In New York sat down with Jacobson to learn more about how the company has supported her development and the opportunities for data scientists looking to join a team committed to growth and building a culture of learning.
What has motivated you to improve your technical coding skills? What skills specifically were you looking to gain?
The field of data science changes rapidly. In order to stay on top of the latest trends, it is imperative that one enjoys learning because the learning never stops. For me, some of that motivation comes from a natural curiosity to understand technologies that will shape our future, like ChatGPT.
Additionally, to be able to work with complex data structures in health care, like claims and provider networks, I needed to dive deeper into natural language processing and graph data science. For NLP, I focused on understanding how models can ingest text data. For graph data science, I was keen on finding communities of providers using clustering techniques.
What steps have you taken to learn or hone those skills?
One crucial resource I have used to grow my skills is online data science courses. As mentioned, I took a 10-week machine learning operations course from FourthBrain and found it beneficial to understand technologies related to model production at scale. I have also taken a variety of free courses taught by Andrew Ng through Coursera that focus on advanced disciplines like NLP.
I have found that doing projects, whether at work, for class or out of interest, gave me opportunities to apply what I was learning. Roughly 80 percent of the concepts taught in the operations course were related to what I was doing at work and allowed me to deploy models on a faster timeline. When work projects were not applicable, one free resource for projects that I have used is Kaggle, an online data science community that puts on competitions. I have also volunteered with nonprofit organizations like DataKind to access social good use cases.
Finally, joining communities like FourthBrain and mlops.community has expanded my network and provided me with limitless content. These channels have allowed me to dive deeper into specific topics through experts, podcasts, webinars and Slack.
How has Nayya supported you in your professional development?
While still relatively new to Nayya, I have worked on challenging problems since day one. Here, we provide medical insurance plan recommendations to users based on their health, wealth and preferences. This use case requires a lot of creative thinking around not only how we develop an accurate recommendation system, but how we scale that system across hundreds of customers with thousands of users. I have had the opportunity to play a pivotal role in designing that system as well as given the flexibility to explore external collaborations with AI vendors. Through these partnerships, I have had access to cutting-edge machine learning platforms that, while primarily supporting Nayya’s use case, also provides the ancillary benefit of knowledge-sharing. The company has also supported my development by accommodating my schedule to attend conferences, workshops and online courses.
