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Manager Causal Inference Jobs in Meriden, CT (NOW HIRING)

Yale Cancer Center

Senior Statistician

New Haven, CT · On-site

$80 - $100/hr

... management of nuanced data, creation of supporting data systems, and marshaling of expertise from ... including causal inference and multivariate analysis. * Proficient in one or more programming ...

All JobsCausal Inference JobsManager Causal Inference JobsManager Causal Inference Jobs in Meriden, CT

Manager Causal Inference information

See Meriden, CT salary details

$28.4K

$102.5K

$115.7K

How much do manager causal inference jobs pay per year?

As of Aug 23, 2026, the average yearly pay for manager causal inference in Meriden, CT is $102,494.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,700.00 and $114,200.00 per year, depending on experience, location, and employer.

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 causal inference?

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.

How does a manager 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.
Manager Causal Inference jobs near you
Infographic showing various Manager Causal Inference job openings in Meriden, CT as of August 2026, with employment types broken down into 84% Full Time, 15% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $102,494 per year, or $49.3 per hour.

Postdoctoral Associate Position, Yale School of Public Health and Department of Biostatistics

Yale University

New Haven, CT • On-site

$49K - $66K/yr

Full-time

Re-posted 12 days ago

Yale University rating

8.6

Company rating: 8.6 out of 10

Based on 64 frontline employees who took The Breakroom Quiz

69th of 621 rated colleges and universities

Job description

Description
We are actively recruiting a postdoctoral associate to join the Public Health Data Science and Data Equity (DSDE) research team in the School of Public Health with a primary home in the Department of Biostatistics.
The postdoctoral associate will work with Dr. Bhramar Mukherjee, PhD, the inaugural Senior Associate Dean of Public Health Data Science and Data Equity, Anna M.R. Lauder endowed Professor of Biostatistics, Professor of Chronic Disease Epidemiology, Professor of Statistics and Data Science, with a focus on developing methods and tools for the analysis of electronic health records and real-world healthcare data. There will also be opportunities for collaboration with faculty with experience in cancer and cardiovascular diseases. The position is for one year and is renewable for a second year based on satisfactory performance and progress.
The postdoctoral associate will actively participate in methodological and collaborative research as well as support writing research grants. Professional development will be an integral part of the position. This role enables postdocs to gain expertise in analysis and inference within complex, non-probability observational samples while engaging in exciting applications that harness and integrate data from various sources such as electronic health records, biobanks, registries, etc. The position will also provide a solid foundation to build a research career in academia, government, or industry.
Organization: Yale School of Public Health
Department: Biostatistics
Primary Location: New Haven, CT
Education Level: PhD
Shift: Days, 40 hours/week
Work Modality: Flexible, hybrid working arrangements could be accommodated if needed
Expected Start Date: Flexible, as early as November 1, 2025
Additional information on the Yale School of Public Health, the Department of Biostatistics and the Department of Chronic Disease Epidemiology at the School of Public Health can be found via the links below:
About Us | Yale School Of Public Health
Biostatistics | Yale School of Public Health
Chronic Disease Epidemiology Department | Yale School of Public Health
Qualifications
• Completed doctorate in Biostatistics, Statistics, Data Science, Computer Science, Bioinformatics, or a related field before the start of the appointment
• Strong oral and written communication skills, and the ability to work effectively with a wide range of constituencies in a complex and diverse setting
• Proficiency with statistical computing (e.g., R, Python or C/C++)
• Demonstrated capacity to work both collaboratively and independently
• Strong strategic, analytical, and problem-solving skills
• Strong interpersonal and project management skills to facilitate timely and professional deliverables
• Experience with causal inference, machine learning, and artificial intelligence is desirable
• Experience with clinical, EHR, or biobank data analyses is desirable
Application Instructions
To apply:
Interested individuals should submit a (1) CV, (2) cover letter that addresses their specific interest in this position, skills and experiences directly related to this position, and highlight overall research interests and plan, and (3) contact information for three professional references via Interfolio. Review of applications will begin immediately and will continue until the position is filled.
Please apply online.
Questions regarding this position should be directed to bhramar.mukherjee@yale.edu.

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