Remote Data Scientist, Healthcare AI & Analytics

Premier Professional Systems, Inc.; United States; Remote; USD 72,000 - 120,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

401k plan

Paid time off

Employee incentive plans

Tuition reimbursement

Professional development

Job summary

Premier Professional Systems, Inc. is hiring a Data Scientist to design, implement, and validate machine learning algorithms for a Clinical Decision Support Platform.

You will collaborate with engineers and clinicians, applying statistics, data modeling, and ML methods to uncover insights and prototype product improvements. Responsibilities include algorithm development, data strategy, requirements analysis, knowledge sharing, and data operations.

Qualifications

• Experience applying machine learning to real world problems.
• Track record delivering results in complex cross-functional projects.
• Knowledge of SQL, R and/or Python and associated ML libraries.
• Experience in cloud computing environments.
• Software development in Agile environments.
• Workflow tools such as Luigi or Airflow.
• Healthcare data experience with large datasets.

Responsibilities

• Develop predictive models and algorithms for the platform.
• Explore data and design strategies for initiatives.
• Translate requirements into production-ready features and stories.
• Mentor and share data science practices with colleagues.
• Develop project estimates and improve data workflows.

Skills

ML algorithms

Statistics

Data modeling

SQL

Python

Cloud computing

Agile

Education

Bachelor's degree

Master's degree

Tools

Luigi

Airflow

Job description

Premier Professional Systems, Inc. is hiring a Data Scientist to design, implement, and validate machine learning algorithms for a Clinical Decision Support Platform.

You will collaborate with engineers and clinicians, applying statistics, data modeling, and ML methods to uncover insights and prototype product improvements. Responsibilities include algorithm development, data strategy, requirements analysis, knowledge sharing, and data operations.