Data Scientist - AI/ML

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Day - 08 Hour (United States of America)

The Stanford Medicine Technology and Digital Solutions team was formed to provide the Stanford Medicine community with the most innovative technology services as efficiently as possible. Led by Michael Pfeffer, CIO and Michael Halaas, Chief Operating Officer and Associate Dean in the School of Medicine, the unified organization brings together the best of the School of Medicine and Stanford Health Care IT to enable new opportunities for groundbreaking work and compassionate care. Together, the Technology and Digital Solutions team will work to break down historic organizational barriers to enable even greater collaboration across Stanford Medicine hospital and clinics, and the entire University.

This is a Stanford Health Care job.

A Brief Overview

The Data Scientist will be part of a team building Stanford Health Care's (SHC) solutions incorporating Artificial Intelligence including providing health care solutions in the areas of patient care, medical research and administrative services. This group is designed to bring Artificial Intelligence (AI), predictive algorithms and other emerging machine learning (ML) based innovations in data science into healthcare and will partner closely with individuals across clinical specialties and operations areas to deploy algorithms that can lead to better patient outcomes.

Reporting to the Data Science Director and working closely with Stanford Medicine's inaugural Chief Data Scientist, this role is responsible for developing predictive algorithms and other machine learning (ML) based innovations in data science into healthcare in a safe, ethical and cost-effective manner. The individual will design, implement and support ML models for use in the clinic.

Locations

Stanford Health Care

What you will do

• Build, deploy and maintain AI and ML enabled care workflows. This includes working with others at SHC to design and develop solutions to the problems undertaken by the Data Science group.

• Evaluate tools, platforms and strategies used by the Data Science group to manage the lifecycle of building models from healthcare data.

• Train, develop, and validate researcher-built or vendor provided machine learning algorithms on hospital data with strong quality control checks and bias assessments.

Education Qualifications

• PhD/MS degree in statistics, informatics or related field

Experience Qualifications

• PhD: Experience preferred

• MS Degree: 4+ years of related experience with applied problems

Required Knowledge, Skills and Abilities

• Ability to write code in SQL, R, or Python for processing large datasets in distributed cloud environments, and experience in processing and analyzing healthcare data.

• Experience developing, evaluating, and implementing machine learning models.

• Experience working with clinicians and researchers across disciplines to develop approaches for use in clinical care.

• Experience working in cloud environments or working in a healthcare organization.

• Graduate level understanding of techniques in machine learning, knowledge representation, and artificial intelligence along with a strong understanding of statistics.

• Knowledge of software development, machine learning, and technology infrastructure

• Excellent verbal and written communication skills, strong interpersonal skills, along with demonstrated creativity and latitude in problem solving, including the ability to prioritize and execute multiple competing tasks.

Physical Demands and Work Conditions

Blood Borne Pathogens

• Category II - Tasks that involve NO exposure to blood, body fluids or tissues, but employment may require performing unplanned Category I tasks

These principles apply to ALL employees:

SHC Commitment to Providing an Exceptional Patient & Family Experience

Stanford Health Care sets a high standard for delivering value and an exceptional experience for our patients and families. Candidates for employment and existing employees must adopt and execute C-I-CARE standards for all of patients, families and towards each other. C-I-CARE is the foundation of Stanford's patient-experience and represents a framework for patient-centered interactions. Simply put, we do what it takes to enable and empower patients and families to focus on health, healing and recovery.

You will do this by executing against our three experience pillars, from the patient and family's perspective:

• Know Me: Anticipate my needs and status to deliver effective care

• Show Me the Way: Guide and prompt my actions to arrive at better outcomes and better health

• Coordinate for Me: Own the complexity of my care through coordination

#LI-AK

Equal Opportunity Employer Stanford Health Care (SHC) strongly values diversity and is committed to equal opportunity and non-discrimination in all of its policies and practices, including the area of employment. Accordingly, SHC does not discriminate against any person on the basis of race, color, sex, sexual orientation or gender identity and/or expression, religion, age, national or ethnic origin, political beliefs, marital status, medical condition, genetic information, veteran status, or disability, or the perception of any of the above. People of all genders, members of all racial and ethnic groups, people with disabilities, and veterans are encouraged to apply. Qualified applicants with criminal convictions will be considered after an individualized assessment of the conviction and the job requirements.

Base Pay Scale: Generally starting at $76.90 - $101.91 per hour

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, specialty and training. This pay scale is not a promise of a particular wage.

At Stanford Health Care, we seek to provide patients with the very best in diagnosis and treatment, with outstanding quality, compassion and coordination. With an unmatched track record of scientific discovery, technological innovation and translational medicine, Stanford Medicine physicians are pioneering leading edge therapies today that will change the way health care is delivered tomorrow.

As part of our spirit of discovery, we also leverage our deep relationships with luminary Silicon Valley companies to develop new ways to deliver preeminent patient care.

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