The Department of Ophthalmology at Stanford University School of Medicine is seeking a highly motivated, hard-working, and professional Data Scientist to facilitate research efforts in ophthalmology. The incumbent will be part of the Department of Ophthalmology: however, the position will be in a collaborative environment, engaging with other Stanford faculty and staff across multiple departments, including Biomedical Informatics, Research IT, and Research Informatics Center. The incumbent will work. With a combination of structured and unstructured (text, imaging) data from several sources, including Stanford’s STARR and STARR-OMOP clinical research databases, the ophthalmology IRIS (Intelligent Research In Sight) national clinical data registry, commercial and Medicare claims data, national survey data, and other sources.

The position will require a comfortable incumbent working with some independence; consulting with and advising investigators to refine research questions, define hypotheses and project objectives, design studies, and devise analysis plans; and working with project team members—including clinicians, trainees, and other statisticians/informaticists—to implement analysis plans and publish findings. The incumbent must be proficient at balancing involvement in multiple simultaneous projects and prioritizing to manage competing priorities. The incumbent will work closely with others to interrogate databases to create analytic files, perform quality control and data cleaning, and manage and analyze data. The incumbent must be an excellent and timely communicator, able to present results in oral and written form to clinical investigators.

Duties include:

·       Collect, manage and clean datasets.

·       Employ new and existing tools to interpret, analyze, and visualize multivariate relationships in data.

·       Create databases and reports, develop algorithms and statistical models, and perform statistical analyses appropriate to data and reporting requirements.

·       Use system reports and analyses to identify potentially problematic data, make corrections, and determine root cause for data problems from input errors or inadequate field edits, and suggest possible solutions.

·       Develop reports, charts, graphs and tables for use by investigators and for publication and presentation.

·       Analyze data processes in documentation.

·       Collaborate with faculty and research staff on data collection and analysis methods.

·       Provide documentation based on audit and reporting criteria to investigators and research staff.

·       Communicate with government officials, grant agencies and industry representatives.

* - Other duties may also be assigned

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 4) Convolutional neural networks

- Experience with free-text data (e.g., natural language processing) is a plus, or else willingness to learn

EDUCATION & EXPERIENCE (REQUIRED):

Bachelor's degree or a combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering.

KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):

·       Substantial experience with MS Office and analytical programs.

·       Strong writing and analytical skills.

·       Ability to prioritize workload.

CERTIFICATIONS & LICENSES:

None

PHYSICAL REQUIREMENTS*:

·       Sitting in place at computer for long periods of time with extensive keyboarding/dexterity.

·       Occasionally use a telephone.

·       Rarely writing by hand.

* - 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:

Some work may be performed in a laboratory or field setting.

Additional WORKING CONDITIONS: May work extended or non-standard hours based on project or business cycle needs.

The expected pay range for this position is $64,480 to $93,000 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location, and external market pay for comparable jobs.

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.

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.

How to Apply:

We invite you to apply for this position by clicking on the “Apply for Job” button. To be considered, you must submit a cover letter and résumé along with your online application.

·       Finalist must successfully complete a background check prior to working at Stanford University.

The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory for all duties, tasks, and responsibilities.  Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility.  Employees may also perform other duties as assigned.

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.