Machine Learning Engineer – Health & Nutrition Data Analytics

Overview We're looking for an experienced Machine Learning Engineer to support ongoing research initiatives involving health and nutrition datasets. You'll apply advanced statistical and ML techniques to extract insights from complex, real-world data and help translate findings into clear, actionable outputs for our research team. Responsibilities Analyze diverse health and nutrition-related datasets using AI/machine learning techniques Apply advanced statistical and ML methods, including clustering, logistic regression, random forest, and deep learning models Clean, merge, and manage large, complex datasets (thousands of observations) with missing or incomplete data Apply advanced methodologies for dataset weighting and analysis Develop technical reports, presentations, and other materials for dissemination to stakeholders Collaborate closely with research analysts and scientists on the team Take on additional duties as agreed upon with the project supervisor Required Skills & Experience Proven experience applying machine learning and statistical modeling to real-world datasets (health, nutrition, epidemiological, or related fields preferred) Strong proficiency with clustering, logistic regression, random forest, and deep learning techniques Hands-on experience with data cleaning, wrangling, and merging across large, messy datasets Experience handling missing data and applying appropriate weighting/adjustment methods Proficiency in Python and/or R, with relevant ML libraries (e.g., scikit-learn, TensorFlow/PyTorch, pandas) Strong written and verbal communication skills — able to translate technical findings into reports and presentations for non-technical audiences Comfortable working collaboratively in a research team environment Nice to Have Background or coursework in public health, nutrition science, biostatistics, or epidemiology Experience with survey data or complex sampling designs Familiarity with reproducible research practices (version control, documented pipelines) How to Apply Please share: Relevant past projects involving health/nutrition or similar complex datasets Examples of technical reports or presentations you've produced from ML/statistical analysis Your availability and estimated hours/week for this engagement