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The Data Scientist will work with cutting edge cloud-based services and machine learning algorithms to modernize the way artificial intelligence (AI) is deployed in healthcare. In partnership with clinicians, cloud partners, and business owners the DS will work backwards from business objectives to drive scalable machine learning solutions and pull through the appropriate technology as needed. The incumbent will be a technical leader influencing the analyses and promoting best practices within the team. Responsibilities THE DETAILS Identify the data-analytics problems that offer the greatest opportunities to the organization Determine the correct data sets and variables Collect large sets of structured and unstructured data from disparate sources Clean and validate the data to ensure accuracy, completeness, and uniformity Devise and apply models and algorithms to mine the stores of big data Analyze data to identify patterns and trends Interpret data to discover solutions and opportunities Perform statistical analytical techniques ranging from basic descriptive techniques to advanced regression and multi-variable techniques, using various statistical software programs Communicate findings to stakeholders using visualization and other means Make recommendations for new metrics, apply analytical techniques, and build ML models to improve insights for clinical analytics Maintain an understanding of the latest trends in data science and machine learning Lead development, execution, and validation of highly complex algorithms and predictive models from large sets of data Partner with business subject matter experts to select relevant sources of information and collect necessary data Communicate new knowledge and insights gained from mining and analyzing large data sets Transfer knowledge and concepts to IS and business teams that are implementing the actual system Mentor and work collaboratively with other data scientists on specific projects, improving team infrastructure and participate in methodology and code reviews Research and implement novel ML approaches to accelerate interoperability, knowledge extraction, enterprise search, real-time workflow orchestration, and more This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice. Qualifications SCOPE MEASURES Direct reports: No Indirect reports: No Budget responsibility: No EDUCATION/CREDENTIALS Master's degree in health science-related discipline, public health, statistics, economics, mathematics, healthcare, or related quantitative field from an accredited college or university or equivalent education and experience In lieu of undergraduate degree, the ratio is 1:1 meaning one year of college equals one year of work experience and vice versa JOB-RELATED EXPERIENCE Customarily has at least five years of experience in data mining and statistical analysis Customarily has at least five years of experience with SQL and statistical software packages (Python, R, SAS/SPSS) Technical experience and data management skills including data extraction, transformation, metadata capabilities Advanced proficiency with MS Excel and PowerPoint Experience using business intelligence tools (Tableau/MicroStrategy/Power BI) and data frameworks Track record of publications JOB-RELATED SKILLS/COMPETENCIES Concentra Core Competencies of Service Mentality, Attention to Detail, Sense of Urgency, Initiative and Flexibility Ability to make decisions or solve problems by using logic to identify key facts, explore alternatives, and propose quality solutions Outstanding customer service skills as well as the ability to deal with people in a manner which shows tact and professionalism The ability to properly handle sensitive and confidential information (including HIPAA and PHI) in accordance with federal and state laws and company policies Have a keen ability to analyze, extract, normalize, understand, and label relevant healthcare data Ability to document technical requirements, code comments, and compile white papers to relay technical methodology and key findings Ability to work in a highly collaborative environment with peers that have a range of technical aptitudes to understand business requirements and build analytical solutions to achieve key business goals Passionate about working with data, relentless in focus on quality, have a solution mindset, and focused to answer key healthcare challenges. Excellent verbal and written communication skills Excellent organizational skills and attention to detail Able to multitask, prioritize, and manage time effectively Strong math skills Problem-solving aptitude Intellectual curiosity and inquisitiveness are highly desirable qualities Originally posted on Himalayas