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Quantitative Researcher Machine Learning Jobs in Detroit, MI

General Motors

AI/ML Senior Researcher

Warren, MI

$92K - $117K/yr

AI/ML Senior Researcher - Smart Manufacturing Systems Research Group Who We Are The Materials ... Lead technical work across a broad set of AI domains, including classical machine learning, deep ...

General Motors

AI/ML Senior Researcher

Warren, MI · On-site

$92K - $117K/yr

AI/ML Senior Researcher - Smart Manufacturing Systems Research Group Who We Are The Materials ... Lead technical work across a broad set of AI domains, including classical machine learning, deep ...

Ford Motor Company

Senior Data Scientist

Dearborn, MI · On-site

Accelerate the application of value-added analytics and machine learning into the portfolio of ... Master's degree in quantitative fields, such as Data Science, Engineering, Operations Research ...

GM Financial

Sr Data Scientist

Detroit, MI · On-site

We're committed to AI-powered transformation, using advanced machine learning and automation to ... Operations Research, Industrial Engineering, Computer Science, Physics or similar quantitative ...

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$52K

$118K

$194.5K

How much do quantitative researcher machine learning jobs pay per year?

As of Aug 9, 2026, the average yearly pay for quantitative researcher machine learning in Detroit, MI is $117,969.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,700.00 and $151,000.00 per year, depending on experience, location, and employer.
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Data Science and Machine Learning Senior Associate

KYYBA Inc

Dearborn, MI • On-site

Full-time

Re-posted 29 days ago

Job description

Job Summary:
KYYBA Inc is a company seeking a Data Science and Machine Learning Senior Associate to leverage data science methodologies for predicting and extracting meaningful trends from raw data. The role involves designing and implementing data analysis and machine learning models to support data-driven decision-making.
Responsibilities:
• 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 like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; 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 etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness
• Model Development: Design, develop, and deploy high-performance machine learning models (supervised, unsupervised, and reinforcement learning) to address business needs such as churn prediction, recommendation engines, or demand forecasting
• Experimental Design: Lead the design and analysis of large-scale experiments (A/B testing, multivariate testing) to validate hypotheses and measure the impact of product changes
• Feature Engineering: Architect and implement robust data pipelines and feature engineering processes to improve model accuracy and scalability
• Algorithm Optimization: Evaluate and refine existing algorithms to improve computational efficiency and predictive power
• Stakeholder Influence: Act as a strategic advisor to leadership, translating complex algorithmic outcomes into business-centric narratives that drive ROI
• Technical Leadership: Mentor junior data scientists and contribute to the team’s internal library of best practices, code standards, and research methodologies
• Collaboration with Engineering: Partner with ML Engineers and DevOps to integrate models into production systems, ensuring reliability and monitoring model drift.
Qualifications:
Required:
• 5+ years of experience in a Data Science role, with a proven track record of delivering models that impact business outcomes.
• Expert proficiency in Python (specifically libraries like Pandas, NumPy, Scikit-learn, SciPy) or R.
• Deep understanding of a broad range of ML techniques, including Gradient Boosting (XGBoost/LightGBM), Random Forests, GLMs, and Clustering.
• Ability to manipulate and extract data from complex, multi-terabyte distributed databases.
• Strong foundation in linear algebra, calculus, and advanced statistical inference.
• Experience with version control (Git) and writing clean, modular, and maintainable code.
• Master's Degree
Company:
Kyyba, Inc. Founded in 1998, the company is headquartered in Farmington Hills, USA, with a team of 1001-5000 employees. The company is currently Late Stage.
KYYBA logo

About KYYBA

Sourced by ZipRecruiter

About Kyyba: Founded in 1998 and headquartered in Farmington Hills, MI, Kyyba has a global presence delivering high-quality resources and top-notch recruiting services, enabling businesses to effectively respond to organizational changes and technological advances. At Kyyba, the overall well-being of our employees and their families is important to us. We are proud of our work culture which embodies our core values; incorporating value, passion, excellence, empowerment, and happiness, creates a vibrant and productive atmosphere. We empower our employees with the resources, incentives, and flexibility that they need to support a healthy, balanced, and fulfilling career by providing many valuable benefits and a balanced compensation structure combined with career development.

Industry

Recruiting and staffing services

Company size

501 - 1,000 Employees

Headquarters location

Farmington Hills, MI, US

Year founded

1998

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