Machine Learning Engineer

Machine Learning Engineer – Dearborn, MI

This role involves predicting and extracting meaningful trends and patterns from raw data using advanced analytics, machine learning, statistics, and related techniques.

• Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making.
• Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data-driven decision-making.
• Apply various analytics techniques such as data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms to analyze data and uncover meaningful patterns, relationships, and trends.
• Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation.
• Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques, and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness.

• Data mining and analytics dashboards.
• Algorithms, data/analytics, data analysis, and data science expertise.

• 5+ years of experience in a relevant field.
• Experience undertaking statistical modeling, predictive analytics, and insight generation for the RAV platform.
• Ability to perform deep‑dive analyses on RAV vehicles to detect early indicators and recommend actions to prevent/mitigate RAV.
• Experience executing quick‑turn studies for urgent business questions by mining, managing, and exploring large, high dimensional structured and unstructured datasets such as RAV, quality, repair orders, repeat visits, parts orders/supply, service, warranty claims, and recalls.
• Proficiency in visualizing validation results, analyses, and predictions using Power BI to deliver clear qualitative and quantitative insights.
• Collaborate closely with architects, project managers, data engineers, software engineers, and other data scientists to test pipelines, validate outputs, and launch new platform capabilities and insights into production for maximum business value.
• Communicate, present, and interpret analytical results to non‑technical audiences, cross‑functional teams, and leadership on a regular basis.

• Master's Degree.

• Doctorate.
• Listed salary ranges may vary based on experience, qualifications, and local market. Also, some positions may include bonuses or other incentives.