Explore 5 junior python developer jobs from 2 hiring companies in Rhinebeck, NY, US. Filter by remote, salary, experience, and company, then open any listing to apply.

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Junior Python Developer

Kingston

Poughkeepsie

Port Ewen

Newburgh

Wawarsing

Beacon

Marbletown

New Paltz

Lincoln Park

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Danbury

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Kiryas Joel

Junior Python Developer Jobs

Boehringer Ingelheim

The Clearing House

Remote

Hybrid

Theclearinghouse

<p><b>Position Summary: </b></p><p>This position is for a DevOps Engineer focused on CI/CD tooling for the on-premises and AWS infrastructure. This position will work closely with developers, QC and infrastructure teams to build out our in-house and cloud CI/CD pipelines so that developers can build and deploy applications in a secure manner. This position will also maintain current DevOps tooling at TCH.</p><p></p><p><b>About The Clearing House: </b></p><p>The Clearing House (TCH) is a banking association and payments company that is owned by the largest commercial banks in the United States. TCH owns and operates the core payments system infrastructure in the US and is currently working to modernize that infrastructure by launching a new, ubiquitous, real-time payment system. TCH is the only private-sector ACH and wire operator in the US, clearing and settling nearly $2 trillion in US dollar payments each day, representing half of all commercial ACH and wire volume. TCH has provided critical services to the banking industry since 1853, and today, our core products facilitate services including Direct Deposit of payroll, bill payments, and check image exchange.</p><p></p><p><b>Qualifications Required:</b></p><ul><li>Develop and maintain Ansible playbooks and roles for automated configuration and deployments</li><li>Support infrastructure provisioning and configuration management across environments (dev, QA, staging, production)</li><li>Collaborate with engineering teams to automate repetitive operational tasks</li><li>Help manage CI/CD pipelines (e.g., GitHub Actions, Jenkins, Azure DevOps, GitLab CI)</li><li>Monitor system performance and assist in troubleshooting deployment issues</li><li>Maintain documentation for infrastructure, automation workflows, and deployment processes</li><li>Participate in improving security, scalability, and reliability of systems</li></ul><p></p><p><b>Qualifications desired:</b></p><ul><li>Bachelor’s degree or equivalent professional experience</li><li>Minimum 1 years in a DevOps, with a track record of managing high -traffic production environments</li><li>Initial level proficiency in AWS and/or Azure</li><li>Basic expertise in Docker and Certified Kubernetes skills</li><li>Basic proficiency in Python, Go, or Ruby for creating custom automation tooling and APIs</li><li>Basic understanding of Linux system administration, kernel tuning, and networking protocols (TCP/IP, HTTP/S, DNS)</li></ul><p></p><p><b>Essential Functions and Responsibilities:</b></p><ul><li>Exposure to cloud platforms (AWS, Azure, or GCP)</li><li>Knowledge of Docker or containerization</li><li>Familiarity with Terraform or other IaC tools</li><li>Understanding of YAML/JSON configuration formats</li><li>Experience with monitoring tools (Prometheus, Grafana, etc.)</li></ul><p></p><p><b>Success factors/job competencies:</b></p><p>The successful candidate will have strong technical expertise on a variety of platforms and will be able to contribute to the design, test and implementation of the application. The candidate will need to be detail oriented but also able to understand the overall environment (internally and externally) and interact with and communicate effectively with all levels of the organization and external clients at all levels. The candidate should be a strong team player. The ability to work effectively cross-organizationally and with external clients will be a key factor to success in this role.</p><p></p><p><b>Performance standards:</b></p><ul><li>Complete tasks and projects in a timely manner.</li><li>Demonstrate high levels of professionalism and decorum.</li><li>Demonstrate effective team work.</li><li>Adhere to and support all Tech &amp; Ops and TCH strategic goals.</li><li>Communicate effectively with internal personnel at all levels and with vendors and external clients.</li></ul><p></p><p><b>Physical demands and work environment: </b></p><p>Work is generally sedentary in nature. The working environment is generally favorable. Lighting and temperature are adequate, and there are no hazardous or unpleasant conditions caused by noise, dust, etc. Work is generally performed within an office environment, with standard office equipment available.</p><p></p><p>Employees in this position will report to the office 3 days per week.</p><p>Occasional travel may be required. Onsite work requirements may change at any time.</p>

DevOps Junior Engineer

Develop and maintain Ansible playbooks, support CI/CD across environments, automate tasks, monitor and document infrastructure.

<div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px">Description</H2></div><div><p>The gBDS /Med Data/AI -- Boehringer Ingelheim is seeking a postdoctoral research fellow to help leverage scientifically rigorous digital health technologies that accelerate clinical development across therapeutic areas.  </p>
<p>The fellow will drive innovation in digital endpoints, remote monitoring technologies, and multimodal data analytics to enhance multiple facets of clinical trials—from identifying and recruiting suitable patients to capturing meaningful real-world outcomes such as quality of life, functional capacity, and disease progression. This research-focused role emphasizes translating digital health innovations into, deployable solutions that improve trial outcomes by better understanding patients’ journeys in the real-world setting. Work will be anchored in Boehringer Ingelheim’s core therapeutic areas — e.g. respiratory, cardiovascular-renal-metabolic, oncology, CNS — with digital measures selected/evaluated in the context of clinically meaningful endpoints for those disease areas. </p>
<p> </p>
<p>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.</p></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px">Duties &amp; Responsibilities</H2></div><div><ul>
<li>Under supervisor/s guidance, lead research focused on evaluating , testing, and deploying digital health technologies (wearables, sensors, smartphone apps, patient-reported outcomes) to accelerate clinical development as well as manuscript preparation and submissions </li>
<li>Conduct statistical analysis of multimodal real-world behavioral data to assess associations with key clinical outcomes of interest (e.g., treatment response, disease progression, adherence, data quality, patient phenotypes/stratification, digital endpoint validation, quality of life) <br> </li>
<li>Proactively design and lead the development of reusable, reproducible data analysis pipelines for extracting quality metrics, features, and validated digital endpoints from multimodal clinical trial data </li>
<li>Design and execute validation studies to establish the scientific rigor, reliability, and clinical meaningfulness of digital health measures for trial use (e.g., patient identification/screening, enrollment optimization, quality-of-life assessment, functional outcomes)  </li>
<li>Collaborate with interdisciplinary and cross-functional teams (clinical development, biostatistics, data science, clinical operations, regulatory affairs) to communicate and present research findings through presentations and scientific reports </li>
</ul></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px">Requirements</H2></div><div><ul>
<li>Ph.D. from an accredited institution earned before the start date at Boehringer Ingelheim. Preferred degree in a quantitative field such as biomedical engineering, statistics, computer science, electrical engineering, data science, or a related discipline </li>
<li>Demonstrable proficiency in at least one scripting language (Python or R preferred) and experience writing reusable, version-controlled (Git), and well-documented code </li>
<li>Demonstrated scientific experience in digital health research as evidenced by publications, presentations, or successful digital health project implementations  </li>
<li>Strong background in applied data science, signal processing, time-series analysis, and machine learning/statistics, preferably in healthcare or clinical research domains </li>
<li>Experience analyzing temporal health-related data from digital health applications, wearable/smartphone sensors (e.g., accelerometer, activity, sleep, voice or other physiological/behavioral measures) is strongly preferred </li>
<li>Familiarity with clinical outcome assessment (COA) frameworks and patient-centered measurement, including PRO, ClinRO, ObsRO, and PerfO categories; experience with ePRO/eCOA instruments or FDA PRO Guidance concepts is a plus </li>
<li>Excellent interpersonal, communication, and presentation skills with the ability to work effectively in a dynamic, collaborative, and cross-functional environment </li>
<li>Working knowledge of regulatory frameworks relevant to digital health technologies, including FDA DHT/SaMD guidance, ICH E6 (GCP), and digital endpoint evidentiary standards (e.g., V3+, BEST Resource, DDT qualification pathway); is a plus</li>
</ul>
<p> </p>
<p><u><strong>Eligibility Requirements</strong></u>:</p>
<div> </div>
<ul>
<li>Must be legally authorized to work in the United States without restriction.</li>
<li>Must be willing to take a drug test and post-offer physical (if required).</li>
<li>Must be 18 years of age or older.</li>
</ul></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px"><b>Compensation</b></H2></div><div><p><span style="font-size:11.0pt"><span style="font-family:Calibri">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 <a href="https://www.boehringer-ingelheim.com/us/careers/benefits-rewards">click here.</a></span></span></p>
<p> </p>
<p><span style="font-size:11.0pt;font-family:arial, helvetica, sans-serif">Duration: Two years</span></p>
<p><span style="font-size:11.0pt;font-family:arial, helvetica, sans-serif">Location: Remote (within US)</span></p></div></div></div>

Post Doctoral Medical Fellow - Digital Health, Clinical Development, Clinical Research (Ridgefield, CT, United States, Connecticut)

Post Doctoral Medical Fellow

PhD in a quantitative field; Python or R proficiency; digital health research experience; data science and ML); strong communication; US work authorization.

<div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px"><b>Description</b></H2></div><div><div>
<p>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.  </p>
<p> </p>
<p>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. </p>
<p> </p>
</div>
<p> 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.</p></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px"><b>Duties &amp; Responsibilities</b></H2></div><div><p>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: </p>
<ul>
<li>Integrate multimodal data sources across trial operations and clinical outcomes to parameterize and calibrate simulations (internal trial data + operational metrics + external benchmarks where appropriate). </li>
<li>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.  </li>
<li>Build simulation models incorporating relevant data sources (clinical trial, real world evidence,) for scenario basis planning, and integration via simulation.  </li>
<li>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. </li>
<li>Implement and compare statistical methods relevant to trial robustness under execution realities, including (examples): 
<ul>
<li>missing data mechanisms and sensitivity analyses (MAR/MNAR), </li>
<li>Bayesian models (meta analytic, hierarchical, etc.) </li>
<li>intercurrent events and estimands-aligned strategies, </li>
<li>site-level/random effects and cluster heterogeneity, </li>
<li>treatment effect attenuation due to nonadherence, </li>
<li>informative dropout and time-varying covariates. </li>
</ul>
</li>
<li>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.   </li>
<li>Create reusable, reproducible simulation pipelines (R/Python) for simulation, diagnostics, and reporting—version-controlled, well-tested, and well-documented for long-term sustainability. </li>
<li>Communicate results clearly to cross-functional stakeholders (biostatistics, clinical operations, clinical development, data science) via manuscripts, conference abstracts, internal whitepapers, and presentations. </li>
</ul></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px"><b>Qualifications</b></H2></div><div><ul>
<li>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. </li>
<li>Strong foundation in clinical trial methodology and inference (e.g., GLMs, mixed models, survival analysis, longitudinal models, causal/estimand thinking, multiplicity basics, Bayesian experience). </li>
<li>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. </li>
<li>Familiarity with Monte Carlo simulation, power/operating characteristic evaluation, and principled model checking/validation. </li>
<li>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. </li>
<li>Ability to work in a highly collaborative environment and communicate statistical results to non-statistical stakeholders with clarity and pragmatism.  </li>
<li>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. </li>
</ul>
<p><br><u><strong>Eligibility Requirements</strong></u>:</p>
<ul>
<li>Must be legally authorized to work in the United States without restriction.</li>
<li>Must be willing to take a drug test and post-offer physical (if required).</li>
<li>Must be 18 years of age or older.</li>
</ul>
<p> </p>
<p><span style="text-decoration:underline"><strong>Application Requirements</strong></span></p>
<p>1. Curriculum vitae</p>
<p>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.</p></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px"><b>Compensation</b></H2></div><div><p><span style="font-size:11.0pt"><span style="font-family:Calibri">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 <a href="https://www.boehringer-ingelheim.com/us/careers/benefits-rewards">click here.</a></span></span></p>
<p> </p>
<p><span style="font-size:11.0pt"><span style="font-family:Calibri"><strong>Duration:</strong> Two years</span></span></p>
<p><span style="font-size:11.0pt"><span style="font-family:Calibri"><strong>Location:</strong> Remote (within US)</span></span></p></div></div></div>

Post Doctoral Medical Fellow - Applied Biostatistics, Clinical Trial Simulation (Ridgefield, CT, United States, Connecticut)

PhD in Biostatistics or Statistics; strong trial methodology; R/Python; Monte Carlo; multimodal data; collaboration; initiative.

<div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="word-wrap:break-word"><H2 style="margin:0.0px">Description</H2></div><div><p>The gBDS /Med Data/AI -- Boehringer Ingelheim is seeking a postdoctoral research fellow to help leverage scientifically rigorous digital health technologies that accelerate clinical development across therapeutic areas.  </p>
<p>The fellow will drive innovation in digital endpoints, remote monitoring technologies, and multimodal data analytics to enhance multiple facets of clinical trials—from identifying and recruiting suitable patients to capturing meaningful real-world outcomes such as quality of life, functional capacity, and disease progression. This research-focused role emphasizes translating digital health innovations into, deployable solutions that improve trial outcomes by better understanding patients’ journeys in the real-world setting. Work will be anchored in Boehringer Ingelheim’s core therapeutic areas — e.g. respiratory, cardiovascular-renal-metabolic, oncology, CNS — with digital measures selected/evaluated in the context of clinically meaningful endpoints for those disease areas. </p>
<p> </p>
<p>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.</p></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="word-wrap:break-word"><H2 style="margin:0.0px">Duties &amp; Responsibilities</H2></div><div><ul>
<li>Under supervisor/s guidance, lead research focused on evaluating , testing, and deploying digital health technologies (wearables, sensors, smartphone apps, patient-reported outcomes) to accelerate clinical development as well as manuscript preparation and submissions </li>
<li>Conduct statistical analysis of multimodal real-world behavioral data to assess associations with key clinical outcomes of interest (e.g., treatment response, disease progression, adherence, data quality, patient phenotypes/stratification, digital endpoint validation, quality of life) <br> </li>
<li>Proactively design and lead the development of reusable, reproducible data analysis pipelines for extracting quality metrics, features, and validated digital endpoints from multimodal clinical trial data </li>
<li>Design and execute validation studies to establish the scientific rigor, reliability, and clinical meaningfulness of digital health measures for trial use (e.g., patient identification/screening, enrollment optimization, quality-of-life assessment, functional outcomes)  </li>
<li>Collaborate with interdisciplinary and cross-functional teams (clinical development, biostatistics, data science, clinical operations, regulatory affairs) to communicate and present research findings through presentations and scientific reports </li>
</ul></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="word-wrap:break-word"><H2 style="margin:0.0px">Requirements</H2></div><div><ul>
<li>Ph.D. from an accredited institution earned before the start date at Boehringer Ingelheim. Preferred degree in a quantitative field such as biomedical engineering, statistics, computer science, electrical engineering, data science, or a related discipline </li>
<li>Demonstrable proficiency in at least one scripting language (Python or R preferred) and experience writing reusable, version-controlled (Git), and well-documented code </li>
<li>Demonstrated scientific experience in digital health research as evidenced by publications, presentations, or successful digital health project implementations  </li>
<li>Strong background in applied data science, signal processing, time-series analysis, and machine learning/statistics, preferably in healthcare or clinical research domains </li>
<li>Experience analyzing temporal health-related data from digital health applications, wearable/smartphone sensors (e.g., accelerometer, activity, sleep, voice or other physiological/behavioral measures) is strongly preferred </li>
<li>Familiarity with clinical outcome assessment (COA) frameworks and patient-centered measurement, including PRO, ClinRO, ObsRO, and PerfO categories; experience with ePRO/eCOA instruments or FDA PRO Guidance concepts is a plus </li>
<li>Excellent interpersonal, communication, and presentation skills with the ability to work effectively in a dynamic, collaborative, and cross-functional environment </li>
<li>Working knowledge of regulatory frameworks relevant to digital health technologies, including FDA DHT/SaMD guidance, ICH E6 (GCP), and digital endpoint evidentiary standards (e.g., V3+, BEST Resource, DDT qualification pathway); is a plus</li>
</ul>
<p> </p>
<p><u><strong>Eligibility Requirements</strong></u>:</p>
<div> </div>
<ul>
<li>Must be legally authorized to work in the United States without restriction.</li>
<li>Must be willing to take a drug test and post-offer physical (if required).</li>
<li>Must be 18 years of age or older.</li>
</ul></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="word-wrap:break-word"><H2 style="margin:0.0px"><b>Compensation</b></H2></div><div><p><span style=""><span style="">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 <a href="https://www.boehringer-ingelheim.com/us/careers/benefits-rewards">click here.</a></span></span></p>
<p> </p>
<p><span style="">Duration: Two years</span></p>
<p><span style="">Location: Remote (within US)</span></p></div></div></div>

Post Doctoral Medical Fellow - Digital Health, Clinical Development (Ridgefield, CT, United States, Connecticut)

PhD in a quantitative field; Python or R; digital health research experience; strong data science and ML skills; clinical outcomes knowledge; US work authorization.

<div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="word-wrap:break-word"><H2 style="margin:0.0px"><b>Description</b></H2></div><div><div>
<p>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.  </p>
<p> </p>
<p>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. </p>
<p> </p>
</div>
<p> 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.</p></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="word-wrap:break-word"><H2 style="margin:0.0px"><b>Duties &amp; Responsibilities</b></H2></div><div><p>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: </p>
<ul>
<li>Integrate multimodal data sources across trial operations and clinical outcomes to parameterize and calibrate simulations (internal trial data + operational metrics + external benchmarks where appropriate). </li>
<li>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.  </li>
<li>Build simulation models incorporating relevant data sources (clinical trial, real world evidence,) for scenario basis planning, and integration via simulation.  </li>
<li>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. </li>
<li>Implement and compare statistical methods relevant to trial robustness under execution realities, including (examples): 
<ul>
<li>missing data mechanisms and sensitivity analyses (MAR/MNAR), </li>
<li>Bayesian models (meta analytic, hierarchical, etc.) </li>
<li>intercurrent events and estimands-aligned strategies, </li>
<li>site-level/random effects and cluster heterogeneity, </li>
<li>treatment effect attenuation due to nonadherence, </li>
<li>informative dropout and time-varying covariates. </li>
</ul>
</li>
<li>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.   </li>
<li>Create reusable, reproducible simulation pipelines (R/Python) for simulation, diagnostics, and reporting—version-controlled, well-tested, and well-documented for long-term sustainability. </li>
<li>Communicate results clearly to cross-functional stakeholders (biostatistics, clinical operations, clinical development, data science) via manuscripts, conference abstracts, internal whitepapers, and presentations. </li>
</ul></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="word-wrap:break-word"><H2 style="margin:0.0px"><b>Qualifications</b></H2></div><div><ul>
<li>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. </li>
<li>Strong foundation in clinical trial methodology and inference (e.g., GLMs, mixed models, survival analysis, longitudinal models, causal/estimand thinking, multiplicity basics, Bayesian experience). </li>
<li>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. </li>
<li>Familiarity with Monte Carlo simulation, power/operating characteristic evaluation, and principled model checking/validation. </li>
<li>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. </li>
<li>Ability to work in a highly collaborative environment and communicate statistical results to non-statistical stakeholders with clarity and pragmatism.  </li>
<li>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. </li>
</ul>
<p><br><u><strong>Eligibility Requirements</strong></u>:</p>
<ul>
<li>Must be legally authorized to work in the United States without restriction.</li>
<li>Must be willing to take a drug test and post-offer physical (if required).</li>
<li>Must be 18 years of age or older.</li>
</ul>
<p> </p>
<p><span style="text-decoration:underline"><strong>Application Requirements</strong></span></p>
<p>1. Curriculum vitae</p>
<p>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.</p></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="word-wrap:break-word"><H2 style="margin:0.0px"><b>Compensation</b></H2></div><div><p><span style=""><span style="">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 <a href="https://www.boehringer-ingelheim.com/us/careers/benefits-rewards">click here.</a></span></span></p>
<p> </p>
<p><span style=""><span style=""><strong>Duration:</strong> Two years</span></span></p>
<p><span style=""><span style=""><strong>Location:</strong> Remote (within US)</span></span></p></div></div></div>

Ph.D. in Biostatistics or Statistics; strong clinical trial methodology; proficient in R and/or Python; experience with reproducible workflows; familiarity with Monte Carlo simulations; ability to work independently and collaboratively.

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