Sr. Data Scientist

Must be able to work Pacific Time Zone hours, regardless of physical location.

Education:

Bachelor’s degree in computer science, artificial intelligence, informatics, or a closely related field.

Technical Expertise:

Proficiency in developing and implementing artificial intelligence (AI) and machine learning (ML) algorithms.

Experience in building highly scalable AI systems with multiple dependencies across teams.

Ability to utilize state-of-the-art AI algorithms and apply off-the-shelf AI and data-centric tools.

Expertise in managing and analyzing large datasets, including data cleaning, transformation, and integration.

Data Science Skills:

Strong skills in statistical analysis and deriving insights from patient and environmental data.

Capability to correlate similar data, find actionable results, and search large datasets for usable information.

Experience in creating experimental frameworks for data collection and automation of data processes.

Collaboration and Communication:

Proven ability to work closely with research teams to design analysis specifications, including algorithms and interpretation of results.

Experience in collaborating with programmers and informatics experts to address client needs.

Ability to create clear, concise reports and presentations to communicate analysis results effectively.

Familiarity with healthcare data, including clinical and research outcomes.

Ability to identify creative uses of AI innovations in healthcare research.

Additional Requirements:

Demonstrated ability to stay current on trends in informatics, AI, and ML within the healthcare sector.

Role Overview:

The Data Scientist will derive insights from the vast amounts of patient and environmental data available within our data warehouse. To achieve this goal, novel and creative machine learning and statistical analyses are needed.

The incumbent will work closely with USC researcher teams to design analysis specifications, including input data specifications, data cleaning, algorithms, and interpretation of results.

The incumbent will develop and implement algorithms on existing data warehouse records and may nominate new external data sources to be ingested to the data warehouse to strengthen analyses.

Analyses will address a wide variety of clinical and research outcomes.

The incumbent will research and implement state-of-the-art AI algorithms, apply off-the-shelf AI and data-centric tools, and collect, store, and maintain data.

The successful candidate will have demonstrated competence in developing highly scalable artificial intelligence systems with multiple dependencies across teams.