Conduct research and statistical analysis to support the creation, enhancement, and testing of science models and algorithms
Collaborate with senior scientists and cross functional partners to understand product requirements and incorporate feedback
Contribute to documentation of research methodology, data preparation steps, and model behavior
Learn and apply PROS coding standards, science library modules, and existing pipelines used in research
Participate in internal science seminars and knowledge sharing sessions
Support productization of science modules by developing research prototypes, specifications, and validation methodologies in partnership with the product team.

Master’s degree in Data Science, Computer Science, Statistics, Operations Research, or a related quantitative field
Good understanding of machine learning models, algorithms, and statistical methods
Strong technical foundation in at least one math/stat domain (e.g., probability, optimization, statistical modeling)
Proficiency in Python and familiarity with ML libraries (e.g., NumPy, Pandas, Scikit-learn)
Experience with data visualization tools or libraries (e.g., Matplotlib, Seaborn)
Strong analytical and problem-solving skills with attention to detail
Ability to clearly communicate ideas in writing and verbally, including translating simple technical concepts for non‑technical audiences
Ability to work collaboratively in a fast-paced environment and follow guidance from senior team members
Passion for AI research, innovation, and continuous learning.
Highly Preferred: Experience with PySpark/Pytorch or distributed data processing
Experience in pricing, revenue management, forecasting, or related applied research areas
Experience working with large datasets or conducting exploratory data analysis in a research setting.

Data Scientist I

Key skills