Biostatistician II - Data Science & Biostatistics Unit

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

In order to support DSBU’s (Data Science and Biostatistics Unit) rapid growth in meeting the analysis needs of CHOP’s hundreds of research teams, we are recruiting a Biostatistician II. The biostatistician will work with teams across the Research Institute to clean and manage data, apply statistical methods to data, and interpret results. In particular, this role will work with principal investigators that focus in the fields of cardiology, public health and clinical effectiveness. This position will report to the Biostatistician Supervisor within the DSBU.

Job Responsibilities

Biostatistician II is a moderately independent role that builds upon an entry level position based on demonstrated increase in consistent proficiency of methods application, programming, interpretation, and communication. The role largely works under the supervision of teams that include a more senior statistician/manager and one or more biomedical domain experts. Management of this role is usually provided on a semi-weekly basis with an emphasis on validation, consistency, refinement of communication, and expansion to more complex techniques.

• Consults with team members to determine study design, conduct power calculations, identify appropriate variables and methods, format data, and identify and resolve data anomalies.
• Actively contributes to development of a statistical analysis plan that includes methods, programming procedures, variable definition, and data handling rules and procedures.
• Investigates increasingly complex methods for inclusion into projects.
• Uses SAS to analyze and clean data to build models
• Applies proficient level of statistical programming to clean and interrogate data, view diagnostics elements of data such as underlying distributions and parameters, implement optimal statistical methods, interpret and export key visuals and results.
• Validates and documents methods such that both more senior statisticians and domain experts may understand and replicate.
• Investigates optimal methods for validation and documentation.
• Provides analysis services for grant applications.
• Contributes to academic output of study teams by writing methods, results, and interpretation for manuscript publication, authoring abstracts, and presenting at professional conferences under the guidance of senior staff/manager.
• Recommends protocol, workflow, or data management changes based on results.
• Participates in communication of research methods, implementation, and results to varied audience of clinicians, scientists, analysts, and programmers.
• Contributes to critical assessment of computational and algorithmic approaches to address assigned biomedical research questions.
• Tracks project activities for reporting and billing purposes.

Required Education and Experience

Required Education: Bachelor’s degree

Required Experience:

• Three (3) years of experience with progressively more complex applied statistics.
• Three (3) years applied experience in using one or more common statistical language programs

Preferred Education, Experience & Cert/Lic

Preferred Education: Master’s degree

Preferred Experience:

• Five (5) years of experience with progressively more complex applied statistics.
• Five (5) years applied experience in using one or more common statistical language programs

Additional Technical Requirements

• Proficient in programming and application of common statistical methods in medical and clinical research, such as SAS, STATA, R or another commonly accepted analytical programming language.
• Excellent verbal and written communications skills with the demonstrated ability to explain technical concepts to a lay audience.
• Detail-oriented with excellent validation and documentation skills.
• High level of personal initiative; ability to work independently as well as collaborate in teams and with people from multiple business and scientific areas.
• Proficient in UNIX and/or Windows OS.