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DESIRED QUALIFICATIONS:
- Strong background in machine learning, biostatistics, and bioinformatics
- Intellectually curious; willing and eager to learn new skills
- Experience with large datasets and database use
- Experience with analysis of real-world observational health data (e.g., electronic medical records, insurance claims)
- Manipulation and analyses of complex high-dimensional data
- Ability to perform careful data cleaning and preparation, including: identifying and handling data discrepancies, duplicates, missing values, outliers, etc; developing cohorts of patients based on inclusion and exclusion criteria, such as those based on billing code diagnoses, age or other demographics, length of follow-up, or other characteristics; creating new variables, including coding relevant outcomes, combining sparse variables, normalizing/standardizing variables; merging datasets on multiple key values; reshaping data from long to wide or vice versa as the befits the analysis needs; loading data into analysis programs, saving data into different file formats
- Experience with at least 2 of the following: 1) Machine learning predictive models (gradient boosted trees, random forest etc.); 2) Deep learning neural networks, transfer learning; 3) Hierarchical/multilevel modeling, propensity score matching/weighting
- Experience with free-text data (e.g., natural language processing) is a plus, or else willingness to learn
EDUCATION & EXPERIENCE (REQUIRED):
Master's degree in biostatistics, statistics or related field and at least 3 years of experience.
KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):
- Proficient in R (preferred), or alternatively either SAS or STATA for statistical analyses and visualization.
- Proficient in SQL
- Python experience, including packages such as Jupyter Notebook, matplotlib, pandas, scikit-learn, and either tensorflow/keras or pytorch or both.
- Able to use GitHub, write reusable and well-documented code
- Familiarity with using cloud computing platforms for data analysis, such as Google Cloud Platform and/or Amazon Web Services
- Outstanding ability to communicate in written and oral English how data analyses were performed, to both technical and non-technical audiences.
- Demonstrated excellence in at least one area of expertise, which may include statistical methodology such as missing data, survival analysis, or informatics; statistical computing; database design (e.g., Oracle databases, SQL); predictive modeling (machine learning and deep learning).
CERTIFICATIONS & LICENSES:
None
PHYSICAL REQUIREMENTS*:
- Frequently perform desk-based computer tasks, seated work and use light/ fine grasping.
- Occasionally stand, walk, and write by hand, lift, carry, push pull objects that weigh up to 10 pounds.
* - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.
WORKING CONDITIONS:
May work extended or non-standard hours based on project or business cycle needs.
WORK STANDARDS:
- Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
- Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
- Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, http://adminguide.stanford.edu.
As an organization that receives federal funding, Stanford University has a COVID-19 vaccination requirement that will apply to all university employees, including those working remotely in the United States and applicable subcontractors. To learn more about COVID policies and guidelines for Stanford University Staff, please visit https://cardinalatwork.stanford.edu/working-stanford/covid-19/interim-policies/covid-19-surveillance-testing-policy
Why Stanford is for You
Imagine a world without search engines or social platforms. Consider lives saved through first-ever organ transplants and research to cure illnesses. Stanford University has revolutionized the way we live and enrich the world. Supporting this mission is our diverse and dedicated 17,000 staff. We seek talent driven to impact the future of our legacy. Our culture and unique perks empower you with:
- Freedom to grow. We offer career development programs, tuition reimbursement, or audit a course. Join a TedTalk, film screening, or listen to a renowned author or global leader speak.
- A caring culture. We provide superb retirement plans, generous time-off, and family care resources.
- A healthier you. Climb our rock wall, or choose from hundreds of health or fitness classes at our world-class exercise facilities. We also provide excellent health care benefits.
- Discovery and fun. Stroll through historic sculptures, trails, and museums.
- Enviable resources. Enjoy free commuter programs, ridesharing incentives, discounts and more.
*Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.