Note: The job is a remote job and is open to candidates in USA. Bayside Solutions is recruiting for a contract AI/ML Scientist role; the hiring client is not identified. The role assesses scientific data and analytical methods for downstream machine learning, with a focus on computational biology and AP-MS data in partnership with bioinformatics.
Responsibilities
- Work with bioinformatics and team scientists to define analytical requirements, deliverables, milestones, and acceptance criteria for experimental data that will be used for machine learning
- Assess AP-MS profile similarity and technical reproducibility, considering quantitative support, missingness, controls, and uncertainty
- Evaluate plate and batch effects, distinguishing technical variation from biological differences and experimental confounding
- Support reference-panel pilot design and assess scoring and normalization approaches against agreed validation criteria for AP-MS and other data types
- Assess whether preprocessing preserves biological information and produces suitable inputs for downstream modeling
- Build reproducible analyses and document methods, assumptions, limitations, and provenance
- Support scientific data evaluation and benchmark design as needed
- Communicate findings and unresolved questions, coordinate follow-up with bioinformatics, and align analytical work with team needs
Skills
- Degree in computational biology, bioinformatics, statistics, quantitative biological science, or a related field, or equivalent research experience
- Demonstrated experience analyzing biological assay data and translating scientific requirements into practical analytical workplans
- Strong statistical judgment in assessing reproducibility, experimental controls, batch effects, and measurement uncertainty
- Proficiency in Python or R, with experience building reproducible analyses, maintaining code in Git, and documenting methods
- Experience assessing data quality, missingness, preprocessing assumptions, and the suitability of datasets for downstream analysis
- Working knowledge of machine learning validation, including held-out evaluation, confounding, and risks of information leakage
- Ability to explain uncertainty and analytical tradeoffs clearly and collaborate effectively with bioinformaticians, chemists, and biologists
- Ability to independently execute defined work, meet agreed milestones, incorporate feedback, and handle internal data securely
- Candidates for this position must qualify as a W2 candidate
- Advanced degree in computational biology, bioinformatics, statistics, or a related field
- Experience with quantitative proteomics, AP-MS, or other high-dimensional biological profiling assays
- Experience comparing profile similarity, control-relative scoring, batch correction, or reference-panel validation methods
- Experience with drug discovery, DEL analysis, scientific evidence evaluation, or collaboration between bioinformatics and ML teams
- Experience with Databricks, cloud/HPC workflows, or computational projects in biotechnology
Company Overview