Remote Causal Inference Jobs in New Jersey (NOW HIRING)

RTI Health Solutions (RTI-HS), a wholly owned subsidiary of RTI International, is an independent and internationally recognized research organization. With offices in the US, UK, Spain, France, and Sweden, we provide healthcare consulting and research expertise to optimize decision making for pharmaceutical, biotechnology, and medical device products across the development and marketing lifecycle. Clients rely on our expertise, quality standards, and integrity to guide their product development and regulatory and market access strategies. Our various practice areas include Value, Access, and HEOR; Patient-Centered and Outcomes Research; Epidemiology and Biostatistics; Medical Communications; Global Business Operations; and Strategic Consulting and Growth.

We are currently seeking an Associate Director to join our growing Biostatistics team. In this role, you will perform statistical research tasks of moderate to high technical complexity, with a strong focus on the planning and analysis of patient-reported outcomes and other clinical outcome assessments in clinical trial and real-world data. You will lead the development of statistical analysis plans, oversee and/or conduct analyses, and lead proposal development under limited supervision while collaborating closely with multidisciplinary project teams.

This role may be hybrid or fully remote within the EU/UK are available, with a preference , with Barcelona

As part of the application process, candidates are required to submit a short cover letter outlining their relevant experience and alignment with the role

• Plan, conduct, and document statistical analyses for clinical trials and observational studies, with an emphasis on analysis of patient-reported outcomes.
• Develop simple to moderately complex statistical analysis plans and contribute to more complex SAPs under supervision.
• Write statistical sections of study reports, protocols, and proposals.
• Ensure the quality, accuracy, and timeliness of statistical analyses and programming outputs.
• Provide statistical and methodological solutions to internal, cross-functional project teams.
• Mentor and oversee less experienced staff on selected project tasks.
• Learn and apply new statistical methods in response to evolving project and research needs.
• Contribute to the scientific reputation and professional development of the biostatistics group and prepare presentations for external audiences.

To be successful in this role, you will have strong analytical, organizational, and problem-solving skills; a high level of written and verbal communication skills, and the ability to manage multiple tasks, meet timelines, and work effectively in collaborative team environments.

• Master's degree and at least 6 years of experience, PhD and at least 1 years of experience, or equivalent combination of education and experience.
• Demonstrated programming skills in SAS, including experience developing reproducible analysis pipelines.
• Demonstrated experience analysing patient-reported outcome data in clinical trials including application to the estimand framework .
• Background in biostatistics or related quantitative disciplines.
• Knowledge of Good Clinical Practice (GCP), quality assurance principles, and regulatory environments.

Preferred

• Experience in the pharmaceutical industry.
• Experience interacting with regulatory agencies, including FDA, EMA, or other global health authorities.

• Familiarity with R, machine learning, and natural language processing.
• Experience with causal inference methods (e.g., propensity score methods, weighting, marginal structural models) and external control arms studies.

• Master's degree and at least 6 years of experience, PhD and at least 1 years of experience, or equivalent combination of education and experience.
• Demonstrated programming skills in SAS, including experience developing reproducible analysis pipelines.
• Demonstrated experience analysing patient-reported outcome data in clinical trials including application to the estimand framework .
• Background in biostatistics or related quantitative disciplines.
• Knowledge of Good Clinical Practice (GCP), quality assurance principles, and regulatory environments.

Preferred

• Experience in the pharmaceutical industry.
• Experience interacting with regulatory agencies, including FDA, EMA, or other global health authorities.

• Familiarity with R, machine learning, and natural language processing.
• Experience with causal inference methods (e.g., propensity score methods, weighting, marginal structural models) and external control arms studies.