Thanks for your interest in the Data Scientist (2 Year Fixed Term) position.
Unfortunately this position has been closed but you can search our 418 open jobs by clicking here.
DESIRED
QUALIFICATIONS:
Strong background in machine
learning, biostatistics, and bioinformatics
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, 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 at least two of R,
SAS, SPSS, or STATA for statistical analyses and visualization.
Proficient in SQL
Python experience or willingness to
learn quickly, including packages such as Jupyter
Notebook, matplotlib, pandas, scikit-learn, tensorflow/keras
Able to use GitHub, write reusable
and well-documented code
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 datases, SQL); predictive modeling (machine
learning and deep learning).
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.
