The Department of Ophthalmology at Stanford University is seeking a Data Scientist for a data science research position. The incumbent will be part of a multi-employee lab group and will work with other investigators and clinicians within ophthalmology as well as other departments. Datasets will include national clinical data registry, insurance claims data, survey data, structured and unstructured electronic health record data, free-text clinical note data, and imaging data. The incumbent will work with datasets with hundreds of millions of records,
The position will require an incumbent who is comfortable working with some independence; consulting with and advising investigators to refine research questions, define hypotheses, design studies and devise analysis plans; and working with project team members-including other statistician(s)/informaticians and data scientists, methods content experts, and clinicians-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.
Under minimal supervision, the incumbent will perform the most complex technical work associated with a wide variety of analytical data and may supervise and advise students, trainees, and other statisticians performing data analysis. 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. Present results orally and in written form to clinical investigators. Provide guidance to clinical investigators on design and analysis issues.
Duties include:
• Study design: work directly with investigators and independently identify appropriate statistical approaches to data analyses; assist in study design and proposal development.
• Create analytic files with detailed documentation.
• Select appropriate statistical and informatics tools for addressing a given research question
• Lead research projects, collaborator engagement, and project status updates
• Implement data analysis through statistical and computational programming
- Create data dictionaries and libraries that document how data are housed
- Create non-routine databases and their related information summary; develop algorithms and statistical models; and perform analyses appropriate to complex data and reporting requirements
- Work under consultative or self-initiated direction to assess and produce relevant, standard, or custom information (reports, charts, graphs and tables) from structured and unstructured data sources by querying data repositories and generating the associated information. Distribute and disseminate reports to applicable agencies, researchers, management and other internal end-users
- Mentor collaborators in areas of experimental design, quality control, and statistical and informatics analysis
- Devise methods for identifying data patterns, trends in available information sources using a variety of qualitative and quantitative techniques. Determine and recommend additional data collection and reporting requirements
- Serve as a resource for non-routine inquiries such as requests for statistics or surveys
- Summarize findings orally and in written form.
• Participate in preparation of grant proposals, conference presentations, and peer-reviewed journal articles for publication.
• Oversee and advise lower level staff on analyses
* – Other duties may also be assigned
DESIRED QUALIFICATIONS:
- PhD in biomedical informatics, computer science, biostatistics, health services research, or related field
- Strong background in machine learning, biostatistics and bioinformatics.
- At least 1-2 years of experience in industry or academia as a data scientist, or collaborating with biostatisticians and clinical investigators on research studies
- Experience with large datasets and database use.
- Experience with natural language processing
- Experience in ophthalmology big data research
- Experience with image analysis via machine learning and AI approaches
- Experience with analysis of electronic medical data.
- Manipulation and analyses of complex high-dimensional data.
- Programming (python, R, Javascript, C++) and database skills (SQL) for database manipulation
- Familiarity with statistical packages such as SAS, R, and/or Stata
- Experience with database curation
- Experience with deep learning approaches, e.g., neural networks
- Demonstrated ability to implement machine learning models in scalable format for broad applicability.
- Strong communication and presentation skills.
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 at least two of R, SAS, SPSS, or STATA.
• Skills in descriptive analysis, modeling of data, and graphic interfaces.
• Outstanding ability to communicate technical information to both technical and non-technical audiences.
• Demonstrated excellence in at least one area of expertise, which may include coordinating studies; statistical methodology such as missing data, survival analysis, statistical genetics, or informatics; statistical computing; database design (e.g., expertise in RedCAP or MySQL); graphical techniques (e.g., expertise in Illustrator).
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.
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 expected pay range for this position is $87,000 to $125,000 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.