Data Scientist

RESPONSIBILITIES

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1.   
Works
collaboratively to design, implement and maintain data science models and
applications.

2.   
Works on programs
to apply data science methodologies, including predictive modeling and
machine learning, data analytics and visualization, and usability and design,
to departmental, service line, and enterprise applications and functions.

3.   
Synthesizes
complex data-related problems into actionable business and/or clinical
strategy, and communicate findings to appropriate end-users and stakeholders.

4.   
Assists with the
development of specifications to support the design of new or modified data
science projects, with a focus on data-driven optimization, enhancement, and
development.

5.   
Assists in the
evaluation of projects, systems, and initiatives at the department, service
line, and enterprise level. Ensures projects and their outputs enhance
clinical quality, patient safety, and institutional efficiency, focusing on
all aspects of data science, including data gathering and wrangling,
exploratory data analysis, data modeling and machine learning, and model
implementation and evaluation. Ensures high quality execution of all proposed
projects.

6.   
Knowledgeable in present and planned data science projects
and maintains voice of the customer in all project initiatives.

7.   
Serves as the link
between the clinical staff (customer) requirements and IS capabilities.

8.   
Assists in
ensuring that systems are implemented to support Health System initiatives
and goals to improve the quality of patient care, to maximize patient safety,
and to provide operational efficiencies.

9.   
Serves as a
resource to the Director of Quality Informatics and Program Director of Data
Science.

10.  Demonstrates familiarity with current hospital information
systems.

11.  Performs other duties as assigned.

*ADA Essential Functions

REQUIRED
EXPERIENCE AND QUALIFICATIONS

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Bachelor’s Degree
in Computer Science, Informatics, Statistics, Engineering, Data Science, or
related field, required.  Master’s Degree,
preferred.

·        
Minimum of two (2)
years of post-graduate training or experience involving quantitative data
analysis, required and working with clinical data, data science, and machine
learning, preferred.

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Working
familiarity with basic medical and health information technology concepts,
including standardized terminologies and ontologies and electronic health
records, as well as Data Warehousing and Business Intelligence tools,
required.

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Expertise in
working with SQL relational databases and statistical or general programming
languages (e.g., Python, R), required.

·        
Deep understanding
of statistical and predictive modeling concepts, machine-learning approaches,
clustering and classification techniques, and recommendation and optimization
algorithms.

·        
Strong
interpersonal skills, capable of working collaboratively with clinicians and
administrators.