HTC Global Services

Research Engineer - Prognostics & Applied Data Science

HTC Global Services • $95K — $115K *
Dearborn, MI 48126In-Person
Manufacturing & Automotive
Less than 5 years of experience
Today
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Job Overview by Ladders

Qualifications

  • Master's degree in a relevant field or equivalent experience
  • 4+ years applying statistical methods in data analysis
  • 3+ years of experience in Python and SQL
  • Experience with C++ programming
  • Knowledge of cloud-based data platforms
  • Experience with embedded controls and diagnostics
  • Familiarity with MATLAB and Simulink for modeling

Responsibilities

  • Develop prognostic features from concept to deployment
  • Build physics-informed machine learning models
  • Design Remaining Useful Life models for vehicle subsystems
  • Convert predictive models into C++ for embedded systems
  • Develop digital signal processing pipelines
  • Design and validate fault detection algorithms
  • Analyze large-scale telemetry data using Python and SQL

Benefits

  • Hybrid work flexibility with four days onsite
  • Opportunity to work with cutting-edge automotive technology
  • Collaborative cross-functional team environment
  • Involvement in full development lifecycle from modeling to deployment
  • Exposure to advanced statistical methods and predictive modeling techniques
Full Job Description
Job Title

Research Engineer - Prognostics & Applied Data Science

Overview

We are seeking a Research Engineer with expertise in applied data science, machine learning, and predictive modeling to develop advanced prognostic features for connected vehicle systems. This role focuses on building predictive models, processing large-scale vehicle data, and developing algorithms that support diagnostics, fault detection, and remaining useful life estimation for vehicle components.

This is a hybrid position requiring four days per week onsite.

Key Responsibilities
  • Develop prognostic features from concept through production deployment.
  • Build physics-informed machine learning models that combine first-principles physics with machine learning techniques.
  • Design prognostics and Remaining Useful Life (RUL) models for vehicle subsystems.
  • Convert predictive models into optimized C++ code for embedded vehicle systems.
  • Develop digital signal processing pipelines and time-series analytics for multi-sensor vehicle data.
  • Design and validate fault detection and isolation (FDI) algorithms.
  • Apply statistical methods including causal inference, multivariate analysis, ANOVA, principal component analysis (PCA), clustering, neural networks, and Gaussian regression.
  • Support the complete development lifecycle from modeling and simulation through hardware validation and production deployment.
  • Collaborate with subject matter experts to develop diagnostics and prognostic algorithms for vehicle components and systems.
  • Process and analyze large-scale telemetry data using Python, SQL, Spark, Hadoop, and cloud platforms.
  • Utilize MATLAB, Simulink, and calibration tools to develop and optimize predictive algorithms.
  • Work cross-functionally to support successful implementation of production software.

Required Qualifications
  • Master's degree in Mechanical Engineering, Electrical Engineering, Computer Science, Computer Engineering, Physics, Mathematics, or a related field, or an equivalent combination of education and experience.
  • 4+ years of experience applying statistical methods such as ANOVA, PCA, correspondence analysis, clustering, factor analysis, multivariate analysis, neural networks, causal inference, and Gaussian regression.
  • 3+ years of experience with Python and SQL.
  • Experience with C++ programming.
  • Experience with data science methodologies and cloud-based data platforms.
  • Experience with embedded controls, onboard diagnostics, sensor processing, and physics-based modeling.
  • Experience using numerical modeling and simulation tools such as MATLAB and Simulink.
  • Experience with digital signal processing (DSP), data structures, algorithms, and software engineering principles.
  • Strong analytical, communication, interpersonal, and problem-solving skills.
  • Self-motivated with the ability to work in cross-functional teams.

Preferred Qualifications
  • PhD in Mechanical Engineering, Electrical Engineering, Computer Science, Computer Engineering, Physics, Mathematics, or a related field.
  • Experience in dynamic systems, controls, robotics, or prognostics and health management.
  • Experience developing automotive prognostics using connected vehicle data.
  • Experience applying machine learning methods including time-series forecasting, random forests, clustering, and neural networks.
  • Experience with Python, R, Spark, and Hadoop.
  • Experience developing embedded automotive software using MATLAB and C++.
  • Familiarity with ATI and ETAS calibration tools.
  • Excellent verbal and written communication skills.

#LI-Hybrid #LI-CP1

About HTC Global Services

HTC Global Services is a global provider of IT and Business Process Services and Solutions. Founded in 1990, HTC is headquartered in Troy, Michigan with delivery centers across multiple locations in North America, Europe, India, and Malaysia. HTC is an Inc. 500 Hall of Fame company and has been recognized by numerous industry and trade publications as a top provider of services. HTC has a strong client base of Global 2000 customers. HTC has a strong focus on healthcare, retail, financial services, and automotive verticals. HTC has a strong commitment to corporate social responsibility and has been recognized for its contributions to the community.
Learn more about HTC Global Services
Size
17,575 employees
Industry
Information Technology
Founded
1990
NASDAQ
HTCKF
* Ladders Estimates

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