Data Scientist -- CHADC5832849

6+ Months Contract Onsite in Westbrook - Hybrid (Tuesdays + 1 other day) Seniority: Entry level DS. Will be partnered with more senior members. Fresh Grad is OK - ideally some real world experience Project: ProCyte One hematology analyzer Responsibilities: Will be working on classification and cluster problems All data is tabular data about cells Digging into spreadsheets Will be working with people familiar with platform. Needed: Python / Pandas or other DS library Stats / ML/ Algos TensorFlow - not a MUST have Growth mindset What you can expect: • Develop classification and clustering models on tabular data to support hematology analyzer capabilities • Contribute to model development, evaluation, and iteration under the guidance of a senior data scientist • Partner with senior team members to understand requirements, explore data, and validate model performance • Document your work clearly so it can be reviewed, reproduced, and built upon by the team • Deploy your solutions to edge hardware What you need to succeed: • 0-2 years of experience applying machine learning to real-world problems (internships, research, and coursework projects count) • Strong working knowledge of Python and common data science libraries (pandas, scikit-learn, NumPy) • Solid foundation in statistics, machine learning, and algorithms • Demonstrated understanding of classification and clustering methods for tabular data, including when to apply which approach and how to evaluate results • Curiosity about the data and the underlying generating processes — a habit of asking "why" before reaching for a model • A growth mindset and willingness to learn from more senior team members • Ability to communicate analyses and results clearly to your immediate team • Bachelor's degree in a quantitative field (statistics, computer science, math, engineering, or related); advanced degree a plus Nice to have: • Exposure to deploying ML models on resource-constrained or edge hardware • Familiarity with model optimization techniques (quantization, ONNX, TFLite) • Experience with version control (Git) and collaborative software development practices • Experience modeling data for medical, diagnostic or life sciences applications