... line management; technical and therapeutic area training; peer recognition and total rewards ... Causal inference methods (e.g., propensity score methods, weighting, matching; GLM or GLMM, MMRM ...
... line management; technical and therapeutic area training; peer recognition and total rewards ... Causal inference methods (e.g., propensity score methods, weighting, matching; GLM or GLMM, MMRM ...
... line management; technical and therapeutic area training; peer recognition and total rewards ... Causal inference methods (e.g., propensity score methods, weighting, matching; GLM or GLMM, MMRM ...
... line management; technical and therapeutic area training; peer recognition and total rewards ... Causal inference methods (e.g., propensity score methods, weighting, matching; GLM or GLMM, MMRM ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
Manager Causal Inference information
How does a Manager of Causal Inference typically collaborate with cross-functional teams to drive impactful business insights?
Managers of Causal Inference frequently work alongside data scientists, product managers, engineers, and business leaders to design and execute experiments that reveal the true impact of business decisions. They translate complex statistical findings into actionable recommendations, ensuring stakeholders understand both the methodology and implications. Regularly, they lead discussions on experiment design, data collection strategies, and result interpretation, fostering a culture of evidence-based decision-making across the organization.
What does a Manager Causal Inference do?
A Manager Causal Inference leads teams that analyze data to determine cause-and-effect relationships, often in business, healthcare, or technology settings. They design experiments or use statistical methods to understand how different factors influence outcomes, helping organizations make data-driven decisions. This role typically involves managing projects, overseeing analysts or data scientists, and communicating findings to stakeholders. Strong expertise in statistics, data analysis, and leadership is essential for success in this position.
What are the key skills and qualifications needed to thrive as a Manager of Causal Inference, and why are they important?
To thrive as a Manager of Causal Inference, you need a deep understanding of statistics, econometrics, and experimental design, typically supported by an advanced degree in a quantitative field. Proficiency with data analysis tools such as R, Python, SQL, and specialized causal inference libraries, along with experience using data visualization and project management platforms, is crucial. Strong leadership, communication, and critical thinking skills help you effectively guide teams and translate complex findings to stakeholders. These skills ensure rigorous, actionable insights that drive strategic decision-making and organizational impact.
What are the most commonly searched types of Causal Inference jobs in Kentucky? The most popular types of Causal Inference jobs in Kentucky are:
What are popular job titles related to Manager Causal Inference jobs in Kentucky? For Manager Causal Inference jobs in Kentucky, the most frequently searched job titles are:
What job categories do people searching Manager Causal Inference jobs in Kentucky look for? The top searched job categories for Manager Causal Inference jobs in Kentucky are:
What cities in Kentucky are hiring for Manager Causal Inference jobs? Cities in Kentucky with the most Manager Causal Inference job openings:
Real World Biostatistician - RWE CMH experience
Louisville, KY • On-site
Other
Posted 6 days ago
Syneos Health rating
8.1
Based on 22 frontline employees who took The Breakroom Quiz
32nd of 74 rated pharmaceutical
Job description
Real World Biostatistician - RWE CMH experience
Syneos Health is a leading fully-integrated life sciences services organization built to accelerate customer success. We partner with innovators at every point across the drug development and commercialization continuum, helping them navigate complexity, anticipate change and accelerate progress.
Our Clinical Solutions team members act with a drug development mindset, applying their years of experience and deep expertise to truly understand customer needs and represent those in the solutions we shape.
Whether you join us in a Functional Service Provider partnership or a Full-Service environment, you'll collaborate with passionate problem solvers, innovating as a team to help our customers achieve their goals. We are agile and driven to deliver - for one another, our customers, and, most importantly, for those in need.
Discover what your 25,000 future colleagues already know:
Why Syneos Health
* We are passionate about developing our people, through career development and progression; supportive and engaged line management; technical and therapeutic area training; peer recognition and total rewards program.
* We are committed to building an inclusive culture - where you can authentically be yourself. Central to this is our purpose - Driven to Deliver - which captures the passion of our colleagues to show up each day and shape solutions that have the ability to dramatically impact someone's life.
* We are continuously building the company we all want to work for and our customers want to work with. Why? Because we know that when we bring together smart colleagues from across the world, we can shape the future of healthcare, driving impact for customers and defining the pace of patient progress.
Job Responsibilities
Job Description
Biostatistician - Real-World Evidence (RWE)
Role Overview
We are seeking a biostatistician with strong experience in real-world data (RWD) with observational study design and safety study experience in addition to RWE CMH experience. This role will support evidence generation across multiple therapeutic areas. This role will focus on the design, analysis, and interpretation of observational studies using EMR and claims data toinform:clinical development, HEOR, regulatory strategy, and market access.
Key Responsibilities
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Design and execute real-world evidence (RWE) studies using EMR and claimsdata;Conducting data specs,SAPand protocol with key research objectives
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Develop and apply robust statistical methodologies, including:
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Causal inference methods (e.g., propensity score methods, weighting, matching; GLM or GLMM, MMRM; survival analysis; random forest)
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Trial emulation frameworks
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External control arm development and borrowing strategies
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Perform data analysis using healthcare coding systems (e.g., ICD, NDC)
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Conduct sample size estimation and power calculations for observational and hybrid study designs
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Collaborate cross-functionally with stakeholders across:
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HEOR
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Market Access
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Regulatory
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Clinical Development
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Translate complex analytical results into clear, actionable insights,e.g.powerpointor study report for decision-making
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Support methodological innovation in RWE, including integration of machine learning approaches where appropriate
Required Qualifications
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M.S. or Ph.D. in Biostatistics, Statistics, Epidemiology, or related field
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5 years of experience in RWD/RWE analytics (industry or equivalent)
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Strong experience with EMR and/or claims data
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Proficiencyin healthcare coding systems (e.g., ICD, NDC)
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Programmingexpertisein at least one of: SAS, R, or Python
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Working knowledge with SQL logic and OMOP data structures
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Solid understanding of:
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Causal inference methods
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Observational study design
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Sample size and power considerations
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Some examples: Independently write cohort definitions in SQL logic; Debug data issues e.g., time zero alignment, exposure gaps; Understand concept mapping (ICD SNOMED RxNorm); Translate statisticalestimand censoring rule and data extraction logic
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RWE CMH Experience
Preferred Qualifications
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Ph.D. strongly preferred
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Experience in one or more therapeutic areas:
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Diabetes
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Cardiovascular disease
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Metabolic disorders
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Familiarity with:
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Trial emulation methodologies
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External control borrowing / hybrid designs
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Basic machine learning methods applied to RWD
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Demonstrated ability to work across multiple therapeutic areas (TAs) in a fast-paced environment
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Strong communicationand stakeholder engagement skills
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Advanced (nice-to-have, not alwaysrequired)
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Build reusable cohort pipelines
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Optimizequeries for large-scale databases
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Work across multiple CDMs (OMOP, Sentinel,PCORnet)
Core Competencies
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Analytical rigor and methodological depth
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Cross-functional collaboration
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Ability tooperatewith agility across diverse projects and therapeutic areas
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Clear and effective scientific communication
Get to know Syneos Health
Over the past 5 years, we have worked with 94% of all Novel FDA Approved Drugs, 95% of EMA Authorized Products and over 200 Studies across 73,000 Sites and 675,000+ Trial patients.
No matter what your role is, you'll take the initiative and challenge the status quo with us in a highly competitive and ever-changing environment. Learn more about Syneos Health.
http://www.syneoshealth.com
Additional Information
Tasks, duties, and responsibilities as listed in this job description are not exhaustive. The Company, at its sole discretion and with no prior notice, may assign other tasks, duties, and job responsibilities. Equivalent experience, skills, and/or education will also be considered so qualifications of incumbents may differ from those listed in the Job Description. The Company, at its sole discretion, will determine what constitutes as equivalent to the qualifications described above. Further, nothing contained herein should be construed to create an employment contract. Occasionally, required skills/experiences for jobs are expressed in brief terms. Any language contained herein is intended to fully comply with all obligations imposed by the legislation of each country in which it operates, including the implementation of the EU Equality Directive, in relation to the recruitment and employment of its employees. The Company is committed to compliance with the Americans with Disabilities Act, including the provision of reasonable accommodations, when appropriate, to assist employees or applicants to perform the essential functions of the job.
What Syneos Health employees say
Pay
Benefits
Hours and flexibility
Workplace
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About Syneos Health
Sourced by ZipRecruiter
Industry
Scientific research and development services and marketing
Company size
10,000+ Employees
Headquarters location
Morrisville, NC, US