Sign upLog in

Post Doctoral Medical Fellow - Applied Biostatistics, Clinical Trial Simulation

Boehringer Ingelheim

Ridgefield, CT(remote)

Apply
JOB DETAILS
SALARY
SKILLS
Academic Background, Analysis Skills, Artificial Intelligence (AI), Bayesian Networks, Benchmarking, Biostatistics, Clinical Data, Clinical Outcomes, Clinical Research, Clinical Trial, Code Reviews, Communication Skills, Compensation and Benefits, Cross-Functional, Data Cleaning, Data Modeling, Data Science, Data Sets, Decision Support, Design Evaluation, Drug Development, Feasibility Analysis, Forecasting, Git, Metrics, Model Review, Model Validation, Monte Carlo Method, Operational Audit, Performance Metrics, Publications, Python Programming/Scripting Language, R Programming Language, Recruiting Strategy, Reliability Engineering, Risk, Safety/Work Safety, Sample Design, Simulation, Statistical Modeling, Statistics, Sustainability, Team Player, Unit Test, White Papers
LOCATION
Ridgefield, CT
POSTED
30+ days ago
Description


The gBDS / Med Data/AI, Boehringer Ingelheim is seeking a Postdoctoral Research Fellow to help advance the development of robust clinical trial simulation tools aimed at improving the probability of success for clinical trials by integrating multimodal datasets. This is an applied research and implementation role—focused on evaluating rigorous statistical methodology from the research stage into confirmatory, pivotal clinical studies. It is an exceptional opportunity for candidates looking to bridge academia and industry from a clinical statistical research perspective, working at the intersection of methodological rigor and real-world drug development impact.


The fellow will focus on identifying, integrating, and applying fit-for-purpose methods and data to inform trial design and execution decisions—supporting faster, more reliable studies through improved feasibility assessment, operational risk forecasting, and robust inference under real-world trial constraints. This research role emphasizes reproducible methods, transparent assumptions, and publication-quality statistical work that can be translated into practical tools used by clinical development teams. The ideal candidate is self-driven and motivated—someone who works independently and takes initiative, while benefiting from scientific guidance and a collaborative team environment.


As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies´ success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim´s high regard for our employees.


Duties & Responsibilities


You will work with considerable autonomy, taking ownership of your projects with scientific guidance available from your supervisor/s and the broader team. Core responsibilities include:


+ Integrate multimodal data sources across trial operations and clinical outcomes to parameterize and calibrate simulations (internal trial data + operational metrics + external benchmarks where appropriate).

+ Evaluate and validate clinical trial simulation frameworks that quantify how operational and clinical factors (e.g., recruitment pace, dropout, missing data, site heterogeneity, nonadherence, endpoint variability, protocol deviations) impact probability of success.

+ Build simulation models incorporating relevant data sources (clinical trial, real world evidence,) for scenario basis planning, and integration via simulation.

+ Build scenario engines for trial execution planning (e.g., “what-if” analyses on site mix, monitoring intensity, recruitment strategies, data cleaning rules, visit schedules, or enrichment approaches) and translate results into actionable decision support.

+ Implement and compare statistical methods relevant to trial robustness under execution realities, including (examples):

+ missing data mechanisms and sensitivity analyses (MAR/MNAR),

+ Bayesian models (meta analytic, hierarchical, etc.)

+ intercurrent events and estimands-aligned strategies,

+ site-level/random effects and cluster heterogeneity,

+ treatment effect attenuation due to nonadherence,

+ informative dropout and time-varying covariates.

+ Conduct simulation studies to evaluate design choices (sample size, randomization schemes, interim decision rules, adaptive elements, endpoint definitions) and make predictions using performance metrics such as power, type I error, bias, estimation bias, predictive probabilities, and other operating characteristics.

+ Create reusable, reproducible simulation pipelines (R/Python) for simulation, diagnostics, and reporting—version-controlled, well-tested, and well-documented for long-term sustainability.

+ Communicate results clearly to cross-functional stakeholders (biostatistics, clinical operations, clinical development, data science) via manuscripts, conference abstracts, internal whitepapers, and presentations.


Qualifications


+ Ph.D. in Biostatistics or Statistics (or closely related quantitative discipline) from an accredited institution, awarded prior to start date. This role is designed for recent graduates seeking an applied biostatistics postdoc focused on clinical trial simulation. Candidates with a strong academic background who are motivated to move into industry—and who want a structured yet independent environment to bridge that transition—will be a great fit.

+ Strong foundation in clinical trial methodology and inference (e.g., GLMs, mixed models, survival analysis, longitudinal models, causal/estimand thinking, multiplicity basics, Bayesian experience).

+ Demonstrated ability to program in R and/or Python for statistical modeling and simulation; experience with reproducible workflows (Git, unit testing, code review, literate reporting such as Quarto/RMarkdown/Jupyter) preferred.

+ Familiarity with Monte Carlo simulation, power/operating characteristic evaluation, and principled model checking/validation.

+ Interest or experience working with multimodal trial data including operational metrics (site performance, enrollment curves, deviations) and clinical outcomes data; experience with real-world or observational health data is a plus but not required.

+ Ability to work in a highly collaborative environment and communicate statistical results to non-statistical stakeholders with clarity and pragmatism.

+ Demonstrated capacity to work independently, manage your own research agenda, and roll forward on problems without waiting for constant direction—proactive initiative is a key expectation of this role.


Eligibility Requirements :


+ Must be legally authorized to work in the United States without restriction.

+ Must be willing to take a drug test and post-offer physical (if required).

+ Must be 18 years of age or older.


Application Requirements


1. Curriculum vitae


2. Letter of intent - focusing on how a fellowship at Boehringer Ingelheim can help further your career growth. *Please upload under My Documents, Additional Attachments.


Compensation


This position offers a base salary of $80,000. The position may be eligible for a role specific variable or performance based bonus and or other compensation elements.  For an overview of our benefits please click here. (https://www.boehringer-ingelheim.com/us/careers/benefits-rewards)


Duration: Two years


Location: Remote (within US)
All qualified applicants will receive consideration for employment without regard to a person’s actual or perceived race, including natural hairstyles, hair texture and protective hairstyles; color; creed; religion; national origin; age; ancestry; citizenship status, marital status; gender, gender identity or expression; sexual orientation, mental, physical or intellectual disability, veteran status; pregnancy, childbirth or related medical condition; genetic information (including the refusal to submit to genetic testing) or any other class or characteristic protected by applicable law.

About the Company

B

Boehringer Ingelheim