2023 Experiential Internship - Discovery and Exploratory Statistics (California)

2023 Experiential Internship - Discovery and Exploratory Statistics (California)

Abbvie | Sioux City, IA, 51101, US
Salary Range:$34,000 – $41,000 Salary range estimated by Zippia

Posted 24 days ago

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Description

ABOUT ABBVIE

AbbVie’s mission is to discover and deliver innovative medicines that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people’s lives across several key therapeutic areas: immunology, oncology, neuroscience, eye care, virology, women’s health, and gastroenterology, in addition to products and services across its Allergan Aesthetics portfolio.

For more information about AbbVie, please visit us at www.abbvie.com.

Follow @abbvie on Twitter, Facebook, Instagram, YouTube, and LinkedIn. 

DISCOVERY AND EXPLORATORY STATISTICS INTERNSHIP OVERVIEW

Envision spending your summer working with energetic colleagues and inspirational leaders, all while gaining world-class experience in one of the most dynamic organizations in the pharmaceutical industry. This is a reality for AbbVie’s Experiential Interns.

Discovery and Exploratory Statistics (DIVES) is part of the Data and Statistical Sciences (DSS) group within the Statistical Science and Analytics (SS&A) organization in AbbVie R&D. We provide biostatistical collaborations for various groups in Discovery, Development Sciences, and the exploratory needs in Drug Development. The DIVES group is currently seeking two Interns, one with a focus on control data borrowing and the other with a focus on missing data handling.

Control Data Borrowing

The Intern will support the development of predictive analysis pipeline for early-phase oncology trials with borrowed control. The intern will evaluate a variety of historical oncology trials as well as real-world data resources that can potentially be used for control data borrowing, in a close collaboration with our prediction medicine partners. Another component of the project includes thorough evaluation of the matching method. We expect well-matched controls can greatly improve the robustness and efficiency of predictive biomarker analysis workflows. The enhanced predictive biomarker analysis workflow with borrowed controls can further facilitate our support for the biomarker projects regarding patient selection and treatment decision for early-phase oncology trials within AbbVie.

Missing Data Handling

The Intern will support the development of a unified missing data handling strategy for both PD and predictive biomarker analysis in our internal pharmacodynamic (PD) and predictive biomarker analysis workflows. The Intern will design simulations to evaluate imputation methods to provide guidance for different scenarios under the framework of biomarker analysis workflows. The enhanced PD and predictive biomarker analysis workflow incorporating the missing data strategy can further facilitate our support for the biomarker projects with the objectives of dose selection, mechanism of action (MOA) identification, patient selection and treatment decision for oncology trials within AbbVie.

Key responsibilities could include:

  • Review documentation and R code modules of internal predictive biomarker analysis or missing data handling for PD analysis workflows to gain familiarity with different types of biomarkers
  • Work with Precision Medicine scientists to identify potential historical trials/real world data resources and evaluate the inclusion/exclusion criteria as well as the biomarker/clinical data included in the datasets. Write a guidance document for the control data warehouse including key variables for matching and recommended analysis.

  • Literature and resource review of matching methods for causal inference or current missing data imputation methods

  • Evaluate and compare existing methods for different types of biomarkers and scenarios (through simulation and real example analysis) and decide the final strategy accordingly
  • Apply the data pipeline to an ongoing trial with single treatment arms as a case study
  • Complete code drafting, debugging and robustness testing
  • Integrate R codes for borrowing controls or missing data handling into existing workflows
  • Summarize results and deliver final presentation
  • MINIMUM QUALIFICATIONS

  • Currently enrolled in university, pursuing a PhD in Statistics, Biostatistics, Bioinformatics, or other related field
  • Must be enrolled in university during the internship period

  • Expected graduation date between August 2023 - December 2025

  • Proficiency in R programming
  • Effective communication skills, both oral and written
  • Have a track record of accomplishment
  • PREFERRED QUALIFICATIONS

  • Exposure to biomarker analysis, statistical genetics/genomics

  • Course work of linear and nonlinear mixed effect models, survival analysis, causal inference, deep/machine learning preferred

  • Experience building R packages
  • BENEFITS AND AMENITIES

  • Competitive pay

  • Travel, transportation and lodging support for eligible students

  • Break rooms stocked with complimentary coffee, tea, beverages, snacks, and cold breakfast items
  • Onsite café and fitness center
  • Immersive experience with DIVES ABA (AbbVie Bay Area) team, collaboration, and scientific advances in the birthplace of the biotech industry-South San Francisco, CA
  • EQUAL EMPLOYMENT OPPORTUNITY

    At AbbVie, we value bringing together individuals from diverse backgrounds to develop new and innovative solutions for patients. As an equal opportunity employer, we do not discriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information gender identity or expression, sexual orientation, marital status, protected veteran status, or any other legally protected characteristic.