Apply Statistical Causal Inference: Leverage advanced statistical methods (including causal ... Highly credible in organizational, time management, decision making, and problem-solving skills.
Apply Statistical Causal Inference: Leverage advanced statistical methods (including causal ... Highly credible in organizational, time management, decision making, and problem-solving skills.
Apply Statistical Causal Inference: Leverage advanced statistical methods (including causal ... Highly credible in organizational, time management, decision making, and problem-solving skills.
Apply Statistical Causal Inference: Leverage advanced statistical methods (including causal ... Highly credible in organizational, time management, decision making, and problem-solving skills.
Apply Statistical Causal Inference: Leverage advanced statistical methods (including causal ... Highly credible in organizational, time management, decision making, and problem-solving skills.
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Apply Statistical Causal Inference: Leverage advanced statistical methods (including causal ... Highly credible in organizational, time management, decision making, and problem-solving skills.
Prognostics and Health Management (PHM) * Predictive Maintenance * Remaining Useful Life (RUL ... Causal Inference * Time Series Analysis * Multivariate Analysis * Gaussian Regression Cloud & Big ...
Prognostics and Health Management (PHM) * Predictive Maintenance * Remaining Useful Life (RUL ... Causal Inference * Time Series Analysis * Multivariate Analysis * Gaussian Regression Cloud & Big ...
Perform causal and genetic inference analyses (including Mendelian randomization and mediation ... Experience building reproducible pipelines using workflow managers (Snakemake, Nextflow, or ...
New
Perform causal and genetic inference analyses (including Mendelian randomization and mediation ... Experience building reproducible pipelines using workflow managers (Snakemake, Nextflow, or ...
New
Apply statistical methods including causal inference, multivariate analysis, ANOVA, principal ... Experience in dynamic systems, controls, robotics, or prognostics and health management.
New
Apply statistical methods including causal inference, multivariate analysis, ANOVA, principal ... Experience in dynamic systems, controls, robotics, or prognostics and health management.
New
Vehicle Prognostics - Applied Data Scientist
Dearborn, MI · On-site
$85K - $160K/yr
... Networks, causal inference, Gaussian regression, etc. * 3+ Experience with Python (and related ... Experience in Dynamic Systems, Control, Robotics, Prognostics and Health Management * Familiarity ...
Vehicle Prognostics - Applied Data Scientist
Dearborn, MI · On-site
$85K - $160K/yr
... Networks, causal inference, Gaussian regression, etc. * 3+ Experience with Python (and related ... Experience in Dynamic Systems, Control, Robotics, Prognostics and Health Management * Familiarity ...
Manager, Biostatistics
Warren, MI · Hybrid
We are seeking a Manager to join our Biostatistics team. This position offers the opportunity to ... other methods, for causal inference. The incumbent will co-author any research protocols ...
Manager, Biostatistics
Warren, MI · Hybrid
We are seeking a Manager to join our Biostatistics team. This position offers the opportunity to ... other methods, for causal inference. The incumbent will co-author any research protocols ...
The current staff of 38 includes statisticians, database administrators, data managers, software ... for causal inference, and statistical monitoring approaches. In addition, successful candidates ...
The current staff of 38 includes statisticians, database administrators, data managers, software ... for causal inference, and statistical monitoring approaches. In addition, successful candidates ...
Manager, Predictive Modeling and Machine Learning
Southfield, MI · On-site
$158K - $170K/yr
The Manager of Predictive Modeling & Machine Learning will lead the development and deployment of ... Drive experimentation with emerging techniques (e.g., causal inference, GenAI). Requirements:
Manager, Predictive Modeling and Machine Learning
Southfield, MI · On-site
$158K - $170K/yr
The Manager of Predictive Modeling & Machine Learning will lead the development and deployment of ... Drive experimentation with emerging techniques (e.g., causal inference, GenAI). Requirements:
Senior Manager, Predictive Modeling and Machine Learning
Southfield, MI · On-site
$184K - $270K/yr
The Senior Manager designs and deploys advanced statistical and ML models that inform strategic ... Drive experimentation with emerging techniques (e.g., causal inference, GenAI) Requirements:
Senior Manager, Predictive Modeling and Machine Learning
Southfield, MI · On-site
$184K - $270K/yr
The Senior Manager designs and deploys advanced statistical and ML models that inform strategic ... Drive experimentation with emerging techniques (e.g., causal inference, GenAI) Requirements:
Excellent time management and organization skills. Excellent interpersonal skills and demonstrated ... Experience with causal inference, particularly using structural equation modeling, is considered a ...
Excellent time management and organization skills. Excellent interpersonal skills and demonstrated ... Experience with causal inference, particularly using structural equation modeling, is considered a ...
Senior Data Analyst
Detroit, MI · On-site +1
$96K - $132K/yr
Strong understanding of A/B testing, experimental design, and causal inference techniques. * Experience with MLOps practices, including model deployment, monitoring, and lifecycle management in ...
Senior Data Analyst
Detroit, MI · On-site +1
$96K - $132K/yr
Strong understanding of A/B testing, experimental design, and causal inference techniques. * Experience with MLOps practices, including model deployment, monitoring, and lifecycle management in ...
... 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 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 Michigan? The most popular types of Causal Inference jobs in Michigan are:
What are popular job titles related to Manager Causal Inference jobs in Michigan? For Manager Causal Inference jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Manager Causal Inference jobs in Michigan look for? The top searched job categories for Manager Causal Inference jobs in Michigan are:
What cities in Michigan are hiring for Manager Causal Inference jobs? Cities in Michigan with the most Manager Causal Inference job openings:
Job description
Job Title:
Research Engineer / Scientist
Position Description:
Prognostics Research Engineer: Own the process for prognostic feature development from conceptual to feature deployment to our production vehicles. Pioneer Physics-Informed Machine Learning (PIML): Fuse first-principles physics modeling with advanced machine learning to develop hybrid, high-fidelity prognostic models that capture complex degradation behaviors across both EV and ICE powertrains. Architect Prognostics & RUL Frameworks: Design and deploy state-of-the-art prognostics models to accurately estimate the Remaining Useful Life (RUL) of critical vehicle subsystems, transforming noisy fleet data into actionable maintenance alerts. Deploy Edge Models in C++: Translate complex predictive models into highly optimized, low-latency C++ code, bridging the gap between cloud-based data science and resource-constrained on-board vehicle electronic control units (ECUs). Harness High-Frequency Signal Processing: Architect custom Digital Signal Processing (DSP) pipelines and time-series analytics to extract clean, high-frequency physical signatures from multi-sensor vehicle networks, isolating early-stage wear patterns before they manifest as failures. Design Multi-Sensor Fault Detection & Isolation (FDI): Develop and validate intelligent, multi-sensor anomaly detection frameworks capable of real-time Fault Detection and Isolation (FDI) to ensure vehicle safety, system redundancy, and fault-tolerant control. Apply Statistical Causal Inference: Leverage advanced statistical methods (including causal inference, multivariate analysis, ANOVA, and PCA) to differentiate between mere correlation and true physical root causes of component degradation across massive, connected vehicle fleets. Own the End-to-End Pipeline (HIL to Production): Direct the entire prognostic lifecycle-moving seamlessly from mathematical conceptualization and simulation in MATLAB/Simulink to physical validation on Hardware-in-the-Loop (HIL) benches, prototype vehicles, and ultimately to production vehicle deployment. Synthesize Deep Subsystem Domain Knowledge: Partner closely with EV and ICE component subject matter experts to translate deep physical domain knowledge (thermal, mechanical, chemical, and electrical) into robust on-board and off-board diagnostics. Build Scale with Big Data & Calibration Tools: Ingest and process large-scale telemetry data using Python, SQL, Spark, and Hadoop, while leveraging industry-standard calibration tools (such as ATI and ETAS) to fine-tune algorithms for real-world driving environments. Interact with subject matter experts to understand component/system functions, leverage existing connected vehicle data to model on-board and off-board prognostics algorithms. Operate cross-functionally to ensure successful code implementation on production vehicles.
Skills Required:
C++, ALGORITHMS, Data Science, Google Cloud Platform, Python, SQL, MATLAB modeling the ideal candidate would have leveraged the tools like SQL, data science methods and tools like python on our cloud platform (GCP) or any cloud platform to do modeling.
Experience Required:
Master's in Mechanical, Electrical, Computer Science, Computer engineering, Physics, Mathematics or related fields or a combination of education and equivalent experience
4+ years of experience of practicing statistical methods and their accurate application e.g. ANOVA, principal component analysis, correspondence analysis, k-means clustering, factor analysis, multi-variate analysis, Neural Networks, causal inference, Gaussian regression, etc.
3+ Experience with Python (and related modules), SQL Experience with embedded controls, onboard Diagnostic, Sensor Processing, General First Principles Physics Modeling and simulation using numerical computational tool (e.g. MATLAB, ATI, Simulink)
Experience with Digital Signal Processing (DSP) data structures, algorithms, and software engineering principles Self-motivated, strong analytical, excellent interpersonal and communication skills required
Experience Preferred:
PhD in Mechanical, Electrical, Computer Science, Computer engineering, Physics, Mathematics or related fields or a combination of education and equivalent experience
Experience in Dynamic Systems, Control, Robotics, Prognostics and Health Management Familiarity working with Automotive prognostics feature development using connected vehicle data.
2+ Experience in application of statistical and machine learning methods e.g., ANOVA, PCA, clustering methods, causal inference, time series forecasting, random forest, multi-variate analysis, neural networks, etc.
Expertise in open-source data science technologies such as Python, R, Spark, Hadoop, etc. acquired through college course work, online training and certification or project development.
Experience in software development for automotive controls with hands on experience using MATLAB for large scale data and understanding of programming fundamentals and experience with C++ programming in embedded environments.
ATI and ETAS calibration tool familiarity
Excellent verbal and written skills.
Highly credible in organizational, time management, decision making, and problem-solving skills.
Education Required:
Master's Degree
Education Preferred:
Doctorate
Additional Safety Training/Licensing/Personal Protection Requirements:
Additional Information :
***HYBRID / 4 days per week in the office*** Are you passionate about leveraging modern day data science methodologies/tools to study and predict the degradation or occurrence of a problem in a vehicle component/system? Would you love to accelerate our efforts to build amazing experiences and software products in the Connected Vehicles space - with data? We are seeking top-tier Applied Data Science professionals who are data driven, self - motivated and detail oriented to help develop and deliver breakthrough Prognostic Features.
Research Engineer / Scientist
Position Description:
Prognostics Research Engineer: Own the process for prognostic feature development from conceptual to feature deployment to our production vehicles. Pioneer Physics-Informed Machine Learning (PIML): Fuse first-principles physics modeling with advanced machine learning to develop hybrid, high-fidelity prognostic models that capture complex degradation behaviors across both EV and ICE powertrains. Architect Prognostics & RUL Frameworks: Design and deploy state-of-the-art prognostics models to accurately estimate the Remaining Useful Life (RUL) of critical vehicle subsystems, transforming noisy fleet data into actionable maintenance alerts. Deploy Edge Models in C++: Translate complex predictive models into highly optimized, low-latency C++ code, bridging the gap between cloud-based data science and resource-constrained on-board vehicle electronic control units (ECUs). Harness High-Frequency Signal Processing: Architect custom Digital Signal Processing (DSP) pipelines and time-series analytics to extract clean, high-frequency physical signatures from multi-sensor vehicle networks, isolating early-stage wear patterns before they manifest as failures. Design Multi-Sensor Fault Detection & Isolation (FDI): Develop and validate intelligent, multi-sensor anomaly detection frameworks capable of real-time Fault Detection and Isolation (FDI) to ensure vehicle safety, system redundancy, and fault-tolerant control. Apply Statistical Causal Inference: Leverage advanced statistical methods (including causal inference, multivariate analysis, ANOVA, and PCA) to differentiate between mere correlation and true physical root causes of component degradation across massive, connected vehicle fleets. Own the End-to-End Pipeline (HIL to Production): Direct the entire prognostic lifecycle-moving seamlessly from mathematical conceptualization and simulation in MATLAB/Simulink to physical validation on Hardware-in-the-Loop (HIL) benches, prototype vehicles, and ultimately to production vehicle deployment. Synthesize Deep Subsystem Domain Knowledge: Partner closely with EV and ICE component subject matter experts to translate deep physical domain knowledge (thermal, mechanical, chemical, and electrical) into robust on-board and off-board diagnostics. Build Scale with Big Data & Calibration Tools: Ingest and process large-scale telemetry data using Python, SQL, Spark, and Hadoop, while leveraging industry-standard calibration tools (such as ATI and ETAS) to fine-tune algorithms for real-world driving environments. Interact with subject matter experts to understand component/system functions, leverage existing connected vehicle data to model on-board and off-board prognostics algorithms. Operate cross-functionally to ensure successful code implementation on production vehicles.
Skills Required:
C++, ALGORITHMS, Data Science, Google Cloud Platform, Python, SQL, MATLAB modeling the ideal candidate would have leveraged the tools like SQL, data science methods and tools like python on our cloud platform (GCP) or any cloud platform to do modeling.
Experience Required:
Master's in Mechanical, Electrical, Computer Science, Computer engineering, Physics, Mathematics or related fields or a combination of education and equivalent experience
4+ years of experience of practicing statistical methods and their accurate application e.g. ANOVA, principal component analysis, correspondence analysis, k-means clustering, factor analysis, multi-variate analysis, Neural Networks, causal inference, Gaussian regression, etc.
3+ Experience with Python (and related modules), SQL Experience with embedded controls, onboard Diagnostic, Sensor Processing, General First Principles Physics Modeling and simulation using numerical computational tool (e.g. MATLAB, ATI, Simulink)
Experience with Digital Signal Processing (DSP) data structures, algorithms, and software engineering principles Self-motivated, strong analytical, excellent interpersonal and communication skills required
Experience Preferred:
PhD in Mechanical, Electrical, Computer Science, Computer engineering, Physics, Mathematics or related fields or a combination of education and equivalent experience
Experience in Dynamic Systems, Control, Robotics, Prognostics and Health Management Familiarity working with Automotive prognostics feature development using connected vehicle data.
2+ Experience in application of statistical and machine learning methods e.g., ANOVA, PCA, clustering methods, causal inference, time series forecasting, random forest, multi-variate analysis, neural networks, etc.
Expertise in open-source data science technologies such as Python, R, Spark, Hadoop, etc. acquired through college course work, online training and certification or project development.
Experience in software development for automotive controls with hands on experience using MATLAB for large scale data and understanding of programming fundamentals and experience with C++ programming in embedded environments.
ATI and ETAS calibration tool familiarity
Excellent verbal and written skills.
Highly credible in organizational, time management, decision making, and problem-solving skills.
Education Required:
Master's Degree
Education Preferred:
Doctorate
Additional Safety Training/Licensing/Personal Protection Requirements:
Additional Information :
***HYBRID / 4 days per week in the office*** Are you passionate about leveraging modern day data science methodologies/tools to study and predict the degradation or occurrence of a problem in a vehicle component/system? Would you love to accelerate our efforts to build amazing experiences and software products in the Connected Vehicles space - with data? We are seeking top-tier Applied Data Science professionals who are data driven, self - motivated and detail oriented to help develop and deliver breakthrough Prognostic Features.
About Optimal Health Care
Sourced by ZipRecruiter
Company size
51 - 200 Employees
Headquarters location
Hagerstown, MD, US
Year founded
2008