Platform Predictive Logistics Data Scientist

Sterling Heights, Michigan

Detroit Engineered Products

Key Responsibilities

Develop and implement machine learning-based models and algorithms to predict vehicle components failure and maintenance needs, collecting and analyzing data from various vehicle sensors and systems.
Perform statistical analysis and hypothesis testing.
Collaborate with stakeholders to understand business needs and translate them into data requirements.
Create data visualizations and dashboards to communicate findings to non-technical audiences.
Collaborate with stakeholders to ensure effective implementation of predictive maintenance models.
Continuously monitor and improve the performance of existing models.
Continuously improve predictive maintenance processes and technologies through research and innovation and stay up-to-date with the latest industry trends and technologies and best practices.

Technical skills

Solid knowledge and proven experience with Statistical Analysis, Data Mining, Pattern Recognition, Machine Learning, Deep Learning, Classification, and Clustering,
Experience with data manipulation and analysis using libraries such as Pandas, NumPy, and Scikit-learn.
Solid knowledge and proven experience with complex SQL scripting, queries, and database normalization methods for data extraction and manipulation.
Experience with data visualization tools such as Tableau, Power BI, or Matplotlib.
Knowledge of machine learning frameworks (e.g., TensorFlow, Keras, PyTorch).
Experience with big data technologies such as Hadoop, Spark, or Hive.
Knowledge of Reliability Testing, Risk Analysis: Failure Modes and Effects Analysis (FMEA)
Good programming skills in Python, MATLAB, and C/C .
Knowledge of communication protocols (e.g., CAN, Ethernet).

Date Posted: 06 May 2025