Senior Data Scientist

Elephas•Madison, WI

50d•Onsite

About The Position

Elephas is a growing biotechnology company located in Madison, WI seeking a talented individual to join our team as a Senior Data Scientist. Applicants should be comfortable in a fast-paced and collaborative environment. Candidates should be eager to learn and flexible with an aptitude for understanding and synthesizing scientific and medical information, strong analytical and problem-solving skills. A successful candidate will not only exemplify these skills but also be passionate about improving the lives of cancer patients, grounded and gritty, and an enthusiastic teacher. The Senior Data Scientist will support clinical correlation data modeling, which includes working with data engineers to assess data quality of incoming assay and clinical data, developing bootstraps across different assay versions, engineering features to feed modeling, evaluating different types of modeling approaches, training unsupervised and supervised data models and reporting performance, assimilating, summarizing, and visualizing results, and presenting results to Commercial, RD and Scientific Communications stakeholders.

Requirements

Master’s (+5 years experience) or PhD (+2 years experience) in Data Science, Biostatistics, Bioinformatics, Biomedical Engineering or related field
Strong background in quantitative analysis and statistics
Experience explaining complex data methodologies to non-technical stakeholders
Familiarity with software development life cycle and best practices
Detail-oriented with strong organizational skills

Nice To Haves

1-3 years experience analyzing biomedical datasets is preferred
Experience programming in Python is preferred
Knowledge of machine learning, data science, data mining, data querying, statistics, signal processing, image processing, etc.

Responsibilities

Lead complex, high-visibility data science projects from problem definition through delivery, implementation, ongoing refinement.
Develop and apply advanced statistical, machine learning, and computational methods to biological, experimental, clinical, product, and operational datasets.
Establish robust, reproducible, and maintainable analytical pipelines, models, and tools suitable for broader team use.
Provide input to biomedical research scientist presentations and publications regarding rigorous and appropriate analytic approaches.
Lead complex data presentation to technical and non-technical stakeholders.
Provide technical leadership through code review, methodological guidance, and best-practice development.
Mentor junior and mid-level data scientists, supporting their technical growth, project execution, and decision-making.