Data Scientist - IS-Digital Health (1.0 FTE, Days)

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Data Scientist - IS-Digital Health (1.0 FTE, Days)

At Stanford Children’s Health, we know world-renowned care begins with world-class caring. That's why we combine advanced technologies and breakthrough discoveries with family-centered care. It's why we provide our caregivers with continuing education and state-of-the-art facilities, like the newly remodeled Lucile Packard Children's Hospital Stanford. And it's why we need caring, committed people on our team - like you. Join us on our mission to heal humanity, one child and family at a time.

Job Summary

This paragraph summarizes the general nature, level and purpose of the job.

The Data Scientist role in the Enterprise Analytics group will develop sophisticated analytics to support insight driven interventions in a variety of settings at Stanford Children’s Health. This position will apply principles of deep learning and predictive analytics and combine them with knowledge of clinical practice and operations to improve clinical and business outcomes most notably in the burgeoning area of Digital Health.

The position will involve being hands on with data analysis, curation, modeling and testing. The Data Scientist will mine and analyze complex structured and unstructured data sets and provide insights using advanced statistical models. The Data Scientist will collaborate with other like-minded individuals throughout Stanford Medicine to help operationalize predictive analytics and other machine learning solutions. The Data Scientist will help integrate solutions into clinical and business workflows leveraging systems such as the Electronic Medical Record.

Essential Functions

The essential functions listed are typical examples of work performed by positions in this job classification. They are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Employees may also perform other duties as assigned.

Must perform all duties and responsibilities in accordance with the hospital’s policies and procedures, including its Service Standards and its Code of Conduct.

1. Develop predictive and prescriptive models that can be applied in a healthcare setting.
2. Implement machine learning solutions into existing workflows in Epic Electronic Medical Record.
3. Provide analysis of large, complex data sets including data emanating from our Digital Health program to provide key insights to leaders.
4. Help implement the tools and architecture needed to support machine learning.
5. Work with Data Architecture team to implement models into our Enterprise Data Warehouse.
6. Develop machine learning solutions using established methods such as Bayesian statistical methods, Bayesian networks, NLP, graph models, textual analysis and contextual analysis.
7. Work with Information Systems Clinical Applications team to adopt predictive models into Stanford Children’s Health Epic system.
8. Provide guidance into the data architecture and management strategy needed to support machine learning, including the required predictive analytics toolsets and software needed.
9. Engage in governance/clearing house for prioritizing and overseeing machine learning solutions development and deployment processes.
10. Liaise with the Digital Health group to perform deep analysis of data to provide insights into clinical and business aspects of program.
11. Work with Analytics Information Delivery team to deploy data visualizations of machine learning and other data analytics.

Minimum Qualifications

Any combination of education and experience that would likely provide the required knowledge, skills and abilities as well as possession of any required licenses or certifications is qualifying.

Education: Master’s or PhD degree in a related field such as Mathematics, Computer Science, Engineering, Statistics from an accredited college or University.

Experience: Five (5) years of experience working in analytical role. Two (2) years of experience working in a data scientist or similar role.

License/Certification: None required.

Knowledge, Skills, & Abilities

These are the observable and measurable attributes and skills required to perform successfully the essential functions of the job and are generally demonstrated through qualifying experience, education, or licensure/certification.

1. Knowledge and understanding of machine learning techniques and algorithms such as k-NN, Naïve Bayes, SVM, Decision Forests etc.
2. Strong programming experience in Python or R.
3. Experience in data visualization tools, such as Tableau.
4. Ability to communicate and apply governance protocols with other Data Scientists within federated structure.
5. Working knowledge of healthcare systems and terminology.
6. Experience working with Hadoop or other big data technologies a plus.

Physical Requirements and Working Conditions

The Physical Requirements and Working Conditions in which the job is typically performed are available from the Occupational Health Department. Reasonable accommodations will be made to enable individuals with disabilities to perform the essential functions of the job.

Pay Range

Compensation is based on the level and requirements of the role.

Salary within our ranges may also be determined by your education, experience, knowledge, skills, location, and abilities, as required by the role, as well as internal equity and alignment with market data.

Typically, new team members join at the minimum to mid salary range.

Minimum to Midpoint Range (1.0 FTE): $149,385.60 to $195,312.00.

Equal Opportunity Employer

Lucile Packard Children’s Hospital Stanford 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, LPCH does not discriminate against any person on the basis of race, color, sex, sexual orientation or gender identity, 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, and where applicable, in compliance with the San Francisco Fair Chance Ordinance.