Apply machine learning, deep learning, and artificial intelligence techniques.
Use advanced analytics methods to extract value from business data.
Perform large-scale experimentation and build data-driven models to answer business questions.
Create hypotheses and experiments to identify hidden relationships and construct new analytics methods.
Develop and implement Markov decision process models and healthcare economic models.
Visualize information and develop reports on results of data analysis.
Influence product teams through presentation of data-based recommendations.
Spread best practices to analytics and product teams.
Implement new tools to make data analysis more efficient.
Ability to communicate complex results to technical and non-technical audiences.
Excellent verbal and written communication skills.
Support and comply with the company’s Quality Management System policies and procedures.
Minimum Qualifications
Bachelor’s degree in computer science, data science, information technology, or related field.
3+ years of professional experience working with large datasets for drawing business insights.
1+ years of experience in a data science role.
Professional working knowledge of machine learning; including solving complex business problems, predictive modeling, leveraging both structured and unstructured data sources, relational databases, and SQL.
Professional working knowledge of statistics and modeling techniques.
Fluent in Python or R programming.
Demonstrated ability to learn new technologies.
Proficient in Microsoft Office.
Preferred Qualifications
Master’s degree in science, technology, engineering, mathematics, or related field.
Experience in cloud environments.
Professional working knowledge of distributed computing and big data technologies, such as Spark or related technologies.
Professional working knowledge of statistical methodologies and tools (R, SAS, SPSS, etc.), mathematical optimization, control theory, and time-series analysis.
Professional working knowledge of Natural Language Processing, Information Retrieval, or Recommender Systems.