... causal inference capabilities, and robust data pipelines that support engineering and mission ... Management capabilities. You will help build tools, shape measurement workflows, and deliver ...
... causal inference capabilities, and robust data pipelines that support engineering and mission ... Management capabilities. You will help build tools, shape measurement workflows, and deliver ...
Director AI Evaluation
Danville, PA · On-site
$180 - $280/hr
People‑leadership experience - managing, developing, and growing technical staff; building teams, not just leading projects. * Strong foundation in experimental design and causal inference, with ...
Director AI Evaluation
Danville, PA · On-site
$180 - $280/hr
People‑leadership experience - managing, developing, and growing technical staff; building teams, not just leading projects. * Strong foundation in experimental design and causal inference, with ...
... causal inference capabilities, and robust data pipelines that support engineering and mission ... Management capabilities. You will help build tools, shape measurement workflows, and deliver ...
... causal inference capabilities, and robust data pipelines that support engineering and mission ... Management capabilities. You will help build tools, shape measurement workflows, and deliver ...
... causal inference capabilities, and robust data pipelines that support engineering and mission ... Management capabilities. You will help build tools, shape measurement workflows, and deliver ...
... causal inference capabilities, and robust data pipelines that support engineering and mission ... Management capabilities. You will help build tools, shape measurement workflows, and deliver ...
People management, HR administration, or formal performance evaluations for the analyst team (those ... Causal inference methods appropriate to healthcare settings where full RCTs are often impractical
People management, HR administration, or formal performance evaluations for the analyst team (those ... Causal inference methods appropriate to healthcare settings where full RCTs are often impractical
... causal inference capabilities, and robust data pipelines that support engineering and mission ... Management capabilities. You will help build tools, shape measurement workflows, and deliver ...
... causal inference capabilities, and robust data pipelines that support engineering and mission ... Management capabilities. You will help build tools, shape measurement workflows, and deliver ...
Familiarity with causal inference and/or AI/ML methods, and interest in applying these approaches ... Strong communication and stakeholder-management skills, with demonstrated ability to influence ...
Familiarity with causal inference and/or AI/ML methods, and interest in applying these approaches ... Strong communication and stakeholder-management skills, with demonstrated ability to influence ...
... managed care operations (UM/CM/DM). • Exposure to cloud data platforms (e.g., Azure/Synapse ... A/B testing and causal inference a plus. • Experience supporting value based care, provider ...
... managed care operations (UM/CM/DM). • Exposure to cloud data platforms (e.g., Azure/Synapse ... A/B testing and causal inference a plus. • Experience supporting value based care, provider ...
$129K - $203K/yr
Experience with probabilistic/Bayesian modeling, uncertainty quantification, or causal inference ... Management, Toxicology, Uncertainty QuantificationPreferred Skills: Current Employees apply HERE ...
$129K - $203K/yr
Experience with probabilistic/Bayesian modeling, uncertainty quantification, or causal inference ... Management, Toxicology, Uncertainty QuantificationPreferred Skills: Current Employees apply HERE ...
Build a high-performance culture of experimentation, A/B testing, and causal inference. Governance, Privacy & Compliance * Own data governance, master data management, data quality, and lineage ...
New
Build a high-performance culture of experimentation, A/B testing, and causal inference. Governance, Privacy & Compliance * Own data governance, master data management, data quality, and lineage ...
New
... 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 ...
... 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 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 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.
What are the most commonly searched types of Causal Inference jobs in Pennsylvania? The most popular types of Causal Inference jobs in Pennsylvania are:
What are popular job titles related to Manager Causal Inference jobs in Pennsylvania? For Manager Causal Inference jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Manager Causal Inference jobs in Pennsylvania look for? The top searched job categories for Manager Causal Inference jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Manager Causal Inference jobs? Cities in Pennsylvania with the most Manager Causal Inference job openings:
Other
Posted 8 days ago
Carnegie Mellon University rating
8.6
Based on 24 frontline employees who took The Breakroom Quiz
67th of 618 rated colleges and universities
Job description
What We Do
The SEI's Applied Measurement & Experimentation (AME) team develops analytic workflows, measurement tools, causal inference capabilities, and robust data pipelines that support engineering and mission-focused decision-making. We work closely with subject matter experts and mission stakeholders to produce reliable, reproducible, and trustworthy analytic solutions. Our mission is to help government and industry partners integrate evidence-based insights into high impact decisions by combining statistical rigor, modern data engineering practices, and emerging AI Software Lifecycle Management capabilities. You will help build tools, shape measurement workflows, and deliver analytic insights directly to decision-makers to support mission and engineering outcomes. AME's decision-directed research combines classical statistical methods with AI-supported approaches to produce data workflows, measurement and analytic insights that inform mission and engineering choices.
In AME, you'll work with engineers, mission operators, and analytics experts who rely on trustworthy measurement systems to make high impact decisions. If you value statistical rigor, engineering discipline, and practical analytics, this role lets you shape the evidence leaders use every day. You'll collaborate with people who bring deep mission and technical expertise to build the measurement tools and analytic workflows that guide decisions across government and industry. It's a role for someone who wants their work to matter and who values clarity, reproducibility, and teaming with domain experts to produce reliable insights for decision making.
What You Will Do
As a Senior Applied Measurement & Data Scientist, you will:
Lead analytic projects, including scoping work, and AI/ML enabled designing analytical approaches, coordinating interdisciplinary contributors, managing timelines, and ensuring high-quality technical outcomes that meet mission and engineering needs.
Collaborate on multi-disciplinary efforts, working closely with colleagues and domain experts to refine workflows, build tools, and integrate statistical, machine-learning, and small-language-model results into operational decision-making.
Apply statistical modeling, ML and data science methods to complex real-world datasets, guiding customers in interpreting results and incorporating insights into mission and engineering decisions.
Build, maintain, and enhance analytic software tools including R/Python dashboard applications, analysis environments, automated AI/ML workflows, and robust data pipelines that support repeatable, reliable analytics.
Apply engineering discipline and scientific rigor to data pipelines, infrastructure, and operational analytics to ensure reliability, reproducibility, and trustworthy measurement.
Work with modern infrastructure tooling, learning new technologies as needed to ensure analytic systems operate smoothly and securely.
Explore and apply open-source small-language model (SLM) and generative AI tools to enhance analytic workflows.
Contribute to research papers, technical writing, outreach materials, and present findings to conferences, workshops, internal teams, government customers, and senior leaders.
Requirements
BS with 10+ years, MS with 8+ years, or PhD with 5+ years in data science, statistics, machine learning, computer science, or another quantitative field.
Proficiency in statistical modeling and data science using R or Python.
Experience with Linux/Unix, containerization, or modern data engineering tools, or willingness to learn.
Strong communication skills and ability to present analytic concepts to expert and non-expert audiences.
Willingness to travel (up to ~25%) to CMU/SEI sites, customer locations, and conferences.
You will be subject to a background investigation and must be able to obtain/maintain a DoW security clearance.
Knowledge, Skills, and Abilities
Innovative and inquisitive with ability to imagine novel analytical solutions to problems
Ability to design and evaluate metrics that support trade-off analysis, prioritization, and resource allocation.
Ability to produce clear, action-focused analytic outputs, not just statistical summaries
Demonstrated ability to lead projects, coordinate multidisciplinary teams, manage complex analytic workflows, and deliver high-quality results.
Ability to participate effectively on teams, contributing technical expertise, supporting collaborative decision-making, and maintaining clear communication.
Strong experience applying statistical modeling, data science methods, and reproducible data engineering practices to mission-focused or real-world datasets.
Proficiency in R or Python for building analytic tools, dashboards, and reports.
Familiarity with (or ability to learn): containerization, infrastructure-as-code approaches, Linux/VM administration, relational and graph databases.
Ability to translate SME insights into structured analytic constraints and usable workflows.
Ability to communicate analytic concepts clearly to both technical and non-technical audiences.
Experience with causal inference concepts is welcome but not required; willingness to learn new analytic methods is essential.
Expertise in One or More of the Following
Analytic/dashboard tooling such as Shiny, Dash, or similar frameworks.
Data engineering & infrastructure including pipelines, containerization, infrastructure-as-code, and Linux environments.
Generative AI / Small Language Models including local deployment, Ollama, OpenWebUI.
Software engineering lifecycle practices for analytic tools.
Desired Experience
Experience in U.S. Government / Department of War work and/or with FFRDCs, UARCs and National Labs is a plus.
Experience conducting decision directed analytic research, structuring questions, designing measurement approaches, and producing results that directly inform engineering or mission choices.
Experience publishing or presenting technical research.
Summary
This role is ideal for a data scientist who enjoys combining causal reasoning, analytics, software development, infrastructure support, and SME collaboration, while leading analytic projects and contributing effectively on teams.
Location
Pittsburgh, PA
Job Function
Software/Applications Development/Engineering
Position Type
Staff - Regular
Full time/Part time
Full time
Pay Basis
SalaryMore Information:
The SEI's Applied Measurement & Experimentation (AME) team develops analytic workflows, measurement tools, causal inference capabilities, and robust data pipelines that support engineering and mission-focused decision-making. We work closely with subject matter experts and mission stakeholders to produce reliable, reproducible, and trustworthy analytic solutions. Our mission is to help government and industry partners integrate evidence-based insights into high impact decisions by combining statistical rigor, modern data engineering practices, and emerging AI Software Lifecycle Management capabilities. You will help build tools, shape measurement workflows, and deliver analytic insights directly to decision-makers to support mission and engineering outcomes. AME's decision-directed research combines classical statistical methods with AI-supported approaches to produce data workflows, measurement and analytic insights that inform mission and engineering choices.
In AME, you'll work with engineers, mission operators, and analytics experts who rely on trustworthy measurement systems to make high impact decisions. If you value statistical rigor, engineering discipline, and practical analytics, this role lets you shape the evidence leaders use every day. You'll collaborate with people who bring deep mission and technical expertise to build the measurement tools and analytic workflows that guide decisions across government and industry. It's a role for someone who wants their work to matter and who values clarity, reproducibility, and teaming with domain experts to produce reliable insights for decision making.
What You Will Do
As a Senior Applied Measurement & Data Scientist, you will:
Lead analytic projects, including scoping work, and AI/ML enabled designing analytical approaches, coordinating interdisciplinary contributors, managing timelines, and ensuring high-quality technical outcomes that meet mission and engineering needs.
Collaborate on multi-disciplinary efforts, working closely with colleagues and domain experts to refine workflows, build tools, and integrate statistical, machine-learning, and small-language-model results into operational decision-making.
Apply statistical modeling, ML and data science methods to complex real-world datasets, guiding customers in interpreting results and incorporating insights into mission and engineering decisions.
Build, maintain, and enhance analytic software tools including R/Python dashboard applications, analysis environments, automated AI/ML workflows, and robust data pipelines that support repeatable, reliable analytics.
Apply engineering discipline and scientific rigor to data pipelines, infrastructure, and operational analytics to ensure reliability, reproducibility, and trustworthy measurement.
Work with modern infrastructure tooling, learning new technologies as needed to ensure analytic systems operate smoothly and securely.
Explore and apply open-source small-language model (SLM) and generative AI tools to enhance analytic workflows.
Contribute to research papers, technical writing, outreach materials, and present findings to conferences, workshops, internal teams, government customers, and senior leaders.
Requirements
BS with 10+ years, MS with 8+ years, or PhD with 5+ years in data science, statistics, machine learning, computer science, or another quantitative field.
Proficiency in statistical modeling and data science using R or Python.
Experience with Linux/Unix, containerization, or modern data engineering tools, or willingness to learn.
Strong communication skills and ability to present analytic concepts to expert and non-expert audiences.
Willingness to travel (up to ~25%) to CMU/SEI sites, customer locations, and conferences.
You will be subject to a background investigation and must be able to obtain/maintain a DoW security clearance.
Knowledge, Skills, and Abilities
Innovative and inquisitive with ability to imagine novel analytical solutions to problems
Ability to design and evaluate metrics that support trade-off analysis, prioritization, and resource allocation.
Ability to produce clear, action-focused analytic outputs, not just statistical summaries
Demonstrated ability to lead projects, coordinate multidisciplinary teams, manage complex analytic workflows, and deliver high-quality results.
Ability to participate effectively on teams, contributing technical expertise, supporting collaborative decision-making, and maintaining clear communication.
Strong experience applying statistical modeling, data science methods, and reproducible data engineering practices to mission-focused or real-world datasets.
Proficiency in R or Python for building analytic tools, dashboards, and reports.
Familiarity with (or ability to learn): containerization, infrastructure-as-code approaches, Linux/VM administration, relational and graph databases.
Ability to translate SME insights into structured analytic constraints and usable workflows.
Ability to communicate analytic concepts clearly to both technical and non-technical audiences.
Experience with causal inference concepts is welcome but not required; willingness to learn new analytic methods is essential.
Expertise in One or More of the Following
Analytic/dashboard tooling such as Shiny, Dash, or similar frameworks.
Data engineering & infrastructure including pipelines, containerization, infrastructure-as-code, and Linux environments.
Generative AI / Small Language Models including local deployment, Ollama, OpenWebUI.
Software engineering lifecycle practices for analytic tools.
Desired Experience
Experience in U.S. Government / Department of War work and/or with FFRDCs, UARCs and National Labs is a plus.
Experience conducting decision directed analytic research, structuring questions, designing measurement approaches, and producing results that directly inform engineering or mission choices.
Experience publishing or presenting technical research.
Summary
This role is ideal for a data scientist who enjoys combining causal reasoning, analytics, software development, infrastructure support, and SME collaboration, while leading analytic projects and contributing effectively on teams.
Location
Pittsburgh, PA
Job Function
Software/Applications Development/Engineering
Position Type
Staff - Regular
Full time/Part time
Full time
Pay Basis
SalaryMore Information:
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