Manager, Statistical Programming

1 month ago

Parsippany, United States Source One Technical Solutions Full time

Source One is a consulting services company and we’re currently looking for the following individual to work as a consultant to our direct client, a global pharmaceutical company in Parsippany, NJ. The role will be on-site; however, remote work may be considered.


Job Title: Manager, Statistical Programming (Contractor)

Initial Duration: One year with possible extension

Pay Rate: $64/hr (W-2)

40 hours/week, Mon-Fri


Reason: To work on statistical analysis on several in-house data, including iGOR registry and other claims databases.


Summary: The Manager, Statistical Programming, a hands-on expert-level programmer in SAS and SQL, will lead in programming, managing and analyzing commercial administrative databases, registry cohort, observational studies, and clinical trial studies. The candidate is responsible for programming in numerous data processing steps (cleaning, extracting, merging, etc.) in SAS/SQL/R/Python programming environments. Another critical responsibility for this position is to apply statistical methods to analyze study data with some literacy of the output and results. The candidate will also assist in managing and maintaining clinical databases in prospective registry studies via the web-based platforms of REDCap and OpenClinica.


Working under the guidance of his/her manager, the candidate will process big real-world databases and extract targeted patient cohorts according to eligibility criteria and define various exposures, treatment, outcomes/endpoints. The candidate is also required to apply analytical methods (e.g. propensity score matching, linear regression) to carry out statistical analysis by working with his/her manager as well as independently. The candidate will be responsible for the quality and accuracy of the generated results with little QC. The candidate will also learn to design and develop RW studies to aid in addressing business questions. The candidate has a basic understanding of healthcare databases. With little supervision, the candidate proactively seeks out answers via self-learning and discussion with his/her manager to carry out necessary steps to deliver results.


Responsibilities:

• Process, manage, and carry out analysis on registry studies and large claims databases.

• Learn to apply various statistical methods to RW research and clinical trial studies.

• Demonstrate knowledge of RWE databases (healthcare claims, charge data master, Medicare, EMR) and clinical trial data.

• Assist in developing statistical analysis plans and statistical outputs to support internal business strategy development and external communications via publications in conferences (abstracts, posters) and clinical journals (original, review manuscripts).

• Joggle multiple projects to meet the timeline.

• Learn subject matters and new statistical methods.

• Design and implement the development of macro/library codes (e.g., SAS macros).

• Provide input and contribute into development of the SAS/SQL/R/Python programming environment.


Interaction: This role interacts with numerous teams, including health economic and outcome research, market access, commercial operations and strategy, payer and employer relations, business development and clinical trials, data and statistical programmers, biostatisticians, project management, IT and external vendors.


Education and Experience:

• Master’s degree from an accredited college or university in health economics and outcomes research (with strong analytical skills), statistics, mathematics, psychometrics/psychology, epidemiology, computer science or related fields.

• Minimum 9 years of experience programming in SAS/SQL/R/Python with at least 3-5 year in the pharmaceutical industry.


Qualifications:

• Proven strong and advanced programming and analytical abilities in SAS/SQL/R/Python including:

◦ Data processing/extraction and cleaning with SAS, SQL, R or Python

◦ SAS Macro language

◦ Application of statistical methods to health clinical and economic outcome data

◦ Deliverable outputs that are meaningful and easy to visualize and understand - descriptive data summary, statistical tests, graphical procedures, etc.

◦ Appreciation/understanding/interpretation of the results

• Demonstrate experience in conducting observational research and study design, strengths and limitations

• Proven project management skills

• Good written and oral English communication skills

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