Tamarack Technology, a provider of artificial intelligence (AI)-based automation and business intelligence software designed for the equipment finance industry, has expanded its AI team with the addition of data scientist Khrystyna Voloshyn.
In her role as a data scientist, Voloshyn will support the development and optimization of Tamarack’s suite of AI products. This includes developing algorithms and models to support the machine learning (ML) processes that drive Tamarack Predictors, using ML to classify and categorize customer data, and developing new products and tools to keep Tamarack at the forefront of the industry.
“Khrystyna’s unique combination of expertise in data science, applied mathematics and informatics immediately elevates Tamarack’s AI product offering,” Scott Nelson, president and chief development officer at Tamarack Technology, said. “She understands the intricacies and application of machine learning at a level that very few can. She sees the data in new ways that offer opportunities to dramatically advance the impact of AI and machine learning for companies in the equipment finance industry.”
Voloshyn’s expertise is rooted in dual graduate degrees in data science and applied mathematics/informatics. A Ukrainian native, Voloshyn began her academic career at Ivan Franko National University of Lviv, where she earned both her bachelor’s and master’s degrees in applied mathematics and informatics.
In 2021, she enrolled in the data science graduate program at Johnson & Wales University in Providence, RI. During this period, she worked on a variety of projects that included data cleansing, analyzing variables using descriptive statistics, identifying relationships between variables, eliminating statistically insignificant variables and making predictions using different types of regression and classification models.
After earning her master’s degree in data science, Voloshyn put her expertise to use, serving as an ML/AI engineer intern at Nucleus Life Sciences. In this role, she focused on ensuring the quality and diversity of data to optimize the performance of the language models that power the platform. The data preprocessing efforts involved large and diverse sets of unstructured text data.
Voloshyn held a similar position as an intern data scientist at PatientsLikeMe. In this role, she supported the data science team in the investigation of the best neuro linguistic programming matching and scoring algorithms that were applied to healthcare conversations. She supported lead data scientists in identifying types of analytics to generate desired insights.
Earlier in her career, Voloshyn deepened her skill set and expertise through a number of quality assurance positions at organizations including Symphony Solutions, Newfire Partners and Limelight Networks.
Voloshyn currently resides in Cambridge, MA.
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