Contract * Job #105483 Prognostics Research Engineer Location: Dearborn, MI (Hybrid - 4 Days Onsite ... Causal Inference * Time Series Analysis * Multivariate Analysis * Gaussian Regression Cloud & Big ...
Contract * Job #105483 Prognostics Research Engineer Location: Dearborn, MI (Hybrid - 4 Days Onsite ... Causal Inference * Time Series Analysis * Multivariate Analysis * Gaussian Regression Cloud & Big ...
LSAT Logical Reasoning Tutor
Ann Arbor, MI · Remote
$26 - $40/hr
... inference questions. Ability to explain argument structure, conditional logic, causal reasoning ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...
LSAT Logical Reasoning Tutor
Ann Arbor, MI · Remote
$26 - $40/hr
... inference questions. Ability to explain argument structure, conditional logic, causal reasoning ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...
LSAT Logical Reasoning Tutor
Detroit, MI · Remote
$26 - $40/hr
... inference questions. Ability to explain argument structure, conditional logic, causal reasoning ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...
LSAT Logical Reasoning Tutor
Detroit, MI · Remote
$26 - $40/hr
... inference questions. Ability to explain argument structure, conditional logic, causal reasoning ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...
Contract Causal Inference information
What are some common challenges faced by professionals in contract causal inference roles, and how can they be addressed?
Professionals in contract causal inference roles often encounter challenges such as working with incomplete or messy datasets, ensuring the validity of assumptions in causal models, and effectively communicating complex findings to stakeholders. Addressing these issues typically involves using robust statistical techniques, performing thorough data cleaning, and engaging in transparent documentation of the modeling process. Additionally, collaborating closely with subject matter experts and stakeholders can help clarify project goals and improve the relevance and impact of your analyses.
What is a Contract Causal Inference specialist?
A Contract Causal Inference specialist is a professional who applies statistical and analytical methods to determine cause-and-effect relationships within data, typically on a contractual or project basis. These specialists are often brought in to analyze business, healthcare, or social science data to help organizations make evidence-based decisions. They use techniques such as randomized controlled trials, regression analysis, and propensity score matching to isolate causal impacts. Contract roles are usually temporary and focused on specific projects or questions. This position requires strong statistical knowledge, programming skills, and the ability to communicate findings to non-technical stakeholders.
What are the key skills and qualifications needed to thrive as a Contract Causal Inference Specialist, and why are they important?
To thrive as a Contract Causal Inference Specialist, you need a strong background in statistics, econometrics, or data science, typically with an advanced degree in a quantitative field. Proficiency with statistical software like R, Python, and specialized causal inference packages, as well as experience with data wrangling tools, is essential. Exceptional analytical thinking, clear communication, and attention to detail are valuable soft skills for interpreting results and collaborating with clients. These competencies are vital for delivering robust, actionable insights that drive evidence-based decision-making in a contractual setting.
What is the difference between Contract Causal Inference vs Data Analyst?
| Aspect | Contract Causal Inference | Data Analyst |
|---|---|---|
| Required Credentials | Statistics, Data Science, or related certifications; often advanced degrees | Bachelor's or Master's in Data Science, Statistics, or related fields |
| Work Environment | Research-focused, project-based, often in consulting or academia | Business environments, analyzing data to inform decisions |
| Employer & Industry Usage | Research institutions, consulting firms, tech companies | Corporations, marketing agencies, finance, healthcare |
| Search & Comparison Intent | Understanding causal relationships, research projects | Data analysis, reporting, business insights |
Contract Causal Inference specialists focus on identifying cause-and-effect relationships through research and statistical methods, often in consulting or academic settings. Data Analysts interpret data to generate reports and insights for business decisions. While both roles require data skills, Contract Causal Inference emphasizes causal modeling and research, whereas Data Analysts focus on descriptive and diagnostic analysis.
What are the most commonly searched types of Causal Inference jobs in Detroit, MI? The most popular types of Causal Inference jobs in Detroit, MI are:
What are popular job titles related to Contract Causal Inference jobs in Detroit, MI? For Contract Causal Inference jobs in Detroit, MI, the most frequently searched job titles are:
What job categories do people searching Contract Causal Inference jobs in Detroit, MI look for? The top searched job categories for Contract Causal Inference jobs in Detroit, MI are:
Job description
- Location: Dearborn, Michigan
- Type: Contract
- Job #105483
Prognostics Research Engineer
Location: Dearborn, MI (Hybrid - 4 Days Onsite)
Industry: Automotive Research & Connected Vehicle Technology
Education: Master's Degree Required | PhD Preferred
About the Role
Are you passionate about using data science, machine learning, and engineering principles to solve complex vehicle reliability challenges?
Our client is seeking a Prognostics Research Engineer to develop next-generation predictive maintenance and health-monitoring solutions for connected vehicles. In this role, you will leverage large-scale vehicle data, advanced analytics, physics-based modeling, and machine learning techniques to predict component degradation and estimate Remaining Useful Life (RUL) across both electric and internal combustion engine (ICE) platforms.
This is a unique opportunity to work at the intersection of data science, vehicle diagnostics, embedded software, signal processing, and advanced research, helping bring innovative prognostic technologies from concept to production vehicles.
What You'll Do
- Develop predictive maintenance and prognostic algorithms for vehicle systems and components.
- Build and deploy Remaining Useful Life (RUL) models using machine learning and physics-based approaches.
- Analyze large-scale connected vehicle and telemetry data to identify early indicators of component degradation.
- Design and implement signal processing pipelines for high-frequency sensor data.
- Develop fault detection and anomaly detection algorithms for real-time vehicle monitoring.
- Apply advanced statistical methods including PCA, ANOVA, clustering, neural networks, causal inference, and multivariate analysis.
- Create and validate models using MATLAB, Simulink, Python, and other analytical tools.
- Optimize and deploy predictive models into embedded C++ environments for production vehicle applications.
- Perform Hardware-in-the-Loop (HIL) testing and validation activities.
- Collaborate with engineering subject matter experts across EV, powertrain, controls, software, and vehicle systems teams.
- Utilize cloud platforms and big-data technologies to process and analyze large-scale fleet data.
- Master's Degree in Mechanical Engineering, Electrical Engineering, Computer Science, Computer Engineering, Physics, Mathematics, or a related field.
- 4+ years of experience applying advanced statistical and machine learning techniques.
- 3+ years of experience with Python and SQL.
- Experience with:
- Machine Learning and Data Science
- MATLAB and Simulink
- Embedded Controls and Diagnostics
- Digital Signal Processing (DSP)
- Sensor Processing
- C++ Programming
- Vehicle or System Modeling
- Strong analytical, communication, and problem-solving skills.
- PhD in a related engineering or scientific discipline.
- Experience with:
- Prognostics and Health Management (PHM)
- Predictive Maintenance
- Remaining Useful Life (RUL) Modeling
- Dynamic Systems, Controls, or Robotics
- Connected Vehicle Data Analytics
- Automotive Diagnostics
- Spark, Hadoop, R, and Open-Source Data Science Technologies
- ATI and ETAS Calibration Tools
- Automotive Software Development and Embedded Systems
Programming & Analytics
- Python
- SQL
- C++
- MATLAB
- Simulink
Data Science & Machine Learning
- Neural Networks
- PCA
- ANOVA
- Clustering
- Causal Inference
- Time Series Analysis
- Multivariate Analysis
- Gaussian Regression
Cloud & Big Data
- Google Cloud Platform (GCP)
- Spark
- Hadoop
Automotive & Controls
- Embedded Systems
- Vehicle Diagnostics
- Signal Processing
- HIL Testing
- Prognostics & Health Monitoring
This role offers the opportunity to work on cutting-edge connected vehicle technologies that directly impact the future of automotive reliability, predictive maintenance, and intelligent vehicle health monitoring. You'll collaborate with industry experts while helping develop innovative features that move from research concepts into production vehicles.
Schedule: Hybrid - 4 days onsite per week in Dearborn, MI.
#LI-PS1 #INDOEM
About Epitec
Sourced by ZipRecruiter
Industry
Recruiting and staffing services
Company size
1,001 - 5,000 Employees
Headquarters location
Southfield, MI, US
Year founded
1978