Data Scientist II

University of Florida•Gainesville, FL

41d•$78,000 - $89,000

About The Position

RESEARCH DATA MANAGEMENT This position will be responsible for selecting and applying appropriate informatics methods to answer questions specified in research projects. Expected activities will include the design of data extraction queries, data processing strategies, and data engineering approaches. This position will coordinate multiple tasks to achieve milestone deadlines set by research projects, and comply in a timely manner with administrative requests and requirements. The position will interact and collaborate with a range of experts in database modeling, machine learning, and other advanced analytic processes as well as clinical and domain experts. Additional expertise in software such as Git and databases will be important for successful creation of software and resource sharing in collaborative work. DATA EXTRACTION, PROCESSING, AND ANALYTICS This position will utilize data science and statistical software such as Python, R, and SAS, to analyze and interpret research data. This position will also use other database/analytical software platforms (e.g., MSSQL, Oracle, PostgresSQL) to develop queries. Expertise in SQL and Python programming will be necessary to design and develop scripts for extracting data from multiple sources into a primary data collection center and processing the data into machine learning ready formats. This position will require expertise in data analytic methods, statistical and machine learning algorithms. WRITING REPORTS OF ANALYSES This position will assist in the interpretation of data and compile reports of analyses. ADMINISTRATION OF PROJECTS This position will be responsible for formulating procedures for effective administration of research projects and protection of health information in accordance with University policy, and all applicable state and federal laws.

Requirements

A Bachelor’s Degree in data science, statistics, bioinformatics, analytics, or similar field and three years of experience; Master’s Degree in data science, statistics, bioinformatics, analytics, or similar field and one year of experience; Doctoral Degree in data science, statistics, bioinformatics, analytics, or similar field.
High level of problem-solving skills, excellent interpersonal skills for interacting with faculty, staff, research participants, and healthcare professionals.
Ability to work in a deadline-driven fast paced environment and adaptability to changes.
Ability to establish and maintain working relationships with University, College, healthcare system, and administrative representatives.
Ability to adapt to changes in understanding and direction of research quickly.
Ability to meet grant proposal, reporting, and publication deadlines.

Nice To Haves

Doctorate or master’s degree in outcomes research, statistics, information systems, biomedical informatics or related field and two years of relevant experience.
In-depth knowledge of health outcomes study design.
In-depth knowledge of SQL and Python.
Experience with general statistical software (e.g. R, SAS).
Experience with data science toolkit, including machine learning frameworks (pandas, numpy, scipy, Scikit learn, PyTorch, etc.).
Excellent technical writing and communication skills in English.
Knowledge of basic principles of clinical and data science research.
Ability to plan, organize and coordinate work assignments.
Ability to work effectively and independently.
Ability to communicate effectively verbally and in writing in English.
Ability to establish and maintain effective working relationships with others.

Responsibilities

Selecting and applying appropriate informatics methods to answer questions specified in research projects.
Design of data extraction queries, data processing strategies, and data engineering approaches.
Coordinating multiple tasks to achieve milestone deadlines set by research projects.
Complying with administrative requests and requirements in a timely manner.
Interacting and collaborating with experts in database modeling, machine learning, and clinical/domain experts.
Utilizing data science and statistical software such as Python, R, and SAS to analyze and interpret research data.
Developing queries using database/analytical software platforms (e.g., MSSQL, Oracle, PostgresSQL).
Designing and developing scripts for extracting data from multiple sources into a primary data collection center and processing the data into machine learning ready formats.
Assisting in the interpretation of data and compiling reports of analyses.
Formulating procedures for effective administration of research projects and protection of health information.