Jr. Data Scientist – Machine Learning

Job Description

Jr. Data Scientist | DeWinter Group

The Tone:
This is a contract role at DeWinter Group, located in Westbrook, ME, with a hybrid work setup. Our client, a leader in the healthcare diagnostics industry, develops machine learning solutions for hematology analyzers, focusing on classification and clustering problems. This project is a 6-month engagement within the Machine Intelligence team in R&D, offering an excellent opportunity to build foundational skills in applied machine learning under the guidance of senior experts. The role is critical for contributing to the client’s diagnostic capabilities.

The TL;DR
• Role: Contract / Early Career
• Type: Contract
• Location: Hybrid, Westbrook, ME
• Pay: $40–$48 hourly
• Team: Machine Intelligence team in R&D, under the guidance of senior experts
• Mission: Develop and deploy machine learning solutions for hematology analyzers, specifically addressing classification and clustering problems on tabular data for edge hardware.
• Tech Stack: Python, pandas, scikit-learn, NumPy

What You’ll Actually Do
• Model Development: Develop classification and clustering models on tabular data to support hematology analyzer capabilities.
• Iteration & Evaluation: Contribute to model development, evaluation, and iteration under the guidance of a senior data scientist.
• Collaboration: Partner with senior team members to understand requirements, explore data, and validate model performance.
• Documentation: Document work clearly so it can be reviewed, reproduced, and built upon by the team.
• Deployment: Deploy solutions to edge hardware.

The Must-Haves
• Background: Bachelor’s degree in a quantitative field (statistics, computer science, math, engineering, or related), suitable for an entry-level position.
• Experience: 0-2 years of experience applying machine learning to real-world problems, including internships, research, and coursework projects. Ideal candidates will have a proven track record of successful contract engagements.
• Skills: 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.
• Bonus: An advanced degree is a plus. Candidates should possess a growth mindset, curiosity about the “why” behind data, and the ability to communicate analyses clearly to the team.