Rice University is looking to drive analytics that underpin strategic initiatives, spanning fundraising innovation, operational efficiency, and research enablement.
Requirements
- Python
- SQL
- statistics
- ML
- deep expertise in at least two areas: advanced ensembling and sampling techniques, forecasting, NLP/LLMs, transfer learning, or MLOps
- scikit-learn
- statsmodels
- TensorFlow/PyTorch
- Git
- Apply advanced analytics—clustering, time-series forecasting, NLP/LLMs—with Python, TensorFlow/PyTorch, and Hugging Face
- Exceptional analytical and problem-solving skills, with a deep understanding of advanced statistical analysis and machine learning
Responsibilities
- designing end-to-end ML/AI workflows
- building scalable pipelines
- embedding monitoring and instrumentation
- Execute the ML lifecycle: data ingestion, feature engineering, modeling, validation, deployment, and monitoring
- Architect and implement CI/CD pipelines and containerized deployments (Git, Docker, etc.)
- Develop high-level application designs and direct detailed design work of developers
- Recommend strategies for system monitoring, performance improvements, and capacity planning
Other
- Bachelor’s degree
- 4 years of experience as a Data Scientist or Machine Learning Engineer
- This position is exclusively on-site, necessitating all duties to be performed in-person at Rice University campus (6100 Main Street, Houston, TX).
- Develop training materials and lead workshops to ensure sustainable adoption and measurable impact against project KPIs.
- collaborating with domain experts, building pipelines, and leading training sessions for non-technical users.
