Data Scientist

Ford • Dearborn, MI

11h • $128,710 - $182,339 • Hybrid

About The Position

Note, this is a hybrid position whereby the employee will work both from home and from the Dearborn office. Hence, the employee must live within a reasonable commuting distance from Dearborn, MI. Utilizing Regression and Machine Learning Model Development for site traffic analysis. Utilizing Natural Language Processing, linear and logistic regression, decision trees, gradient boosting, and feature importance models. Designing multivariate experiments to measure site KPIs, such as conversion metrics. Performing post-test hypothesis testing. Applying ANOVA, Bayesian statistical analysis, regression principles, and statistical techniques for data analysis. Providing actionable business insights and decision support for site updates based on statistical analysis. Building, testing, implementing and analyzing A/B and multivariate testing programs. Communicating statistical and technical topics to non-technical business partners. Utilizing Python (Pandas, SciPi, ScikitLearn, NLTK, Keras, Tensorflow, and Statsmodels), and R. Utilizing SQL for data mining, including writing database queries for performance efficiency, including utilizing table indices and implementing database techniques to reduce cardinality, create tables, and partition data. Master's degree or foreign equivalent in Electronic Engineering, Data Analytics or related field and 4 years of experience in the job offered or related occupation. 4 years of experience with each of the following skills is required: 1. Applying Python (including Pandas, SciPy, Scikit-learn, NLTK, Keras, TensorFlow, and Statsmodels) as the primary language for data manipulation, statistical modeling, and developing machine/deep learning solutions using large-scale datasets from automotive manufacturing processes, vehicle telematics, quality control systems, or supply chain operations. 2. Creating, developing and implementing Machine Learning & Deep Learning models to solve critical problems specific to automobile manufacturing, including predictive maintenance for factory equipment or vehicles, predicting production quality issues, optimizing assembly line efficiency, or analyzing complex sensor data from production or vehicle systems. 3. Utilizing SQL for data mining to query and extract data from large relational databases containing manufacturing data, supply chain information, warranty claims data, or vehicle performance logs to support analysis and modeling activities. 4. Employing statistical methods, including Regression analysis, Bayesian analysis, and ANOVA, to analyze manufacturing process variability, quality control metrics, engineering test outcomes, and operational data, providing statistical insights for production optimization and decision-making. 5. Utilizing Cloud computing platforms including AWS and GCP, or scalable storage, processing, and analysis of large-scale automotive datasets (vehicle sensor data streams and production logs) and deploying data science solutions within a manufacturing or related operational context. 6. Developing and evaluating A/B and multivariate tests to assess the impact of changes to manufacturing processes, internal systems (logistics and quality checks), or vehicle software features on key performance indicators within an automotive environment. 3 years of experience with each of the following skills is required: 1. Utilizing Natural Language Processing (NLP) techniques to analyze unstructured text data from sources critical to automotive operations, including manufacturing defect reports, warranty claims descriptions, maintenance logs, or customer feedback related to vehicles or production issues. We are offering a salary of $128,710.00 - $182,338.56/yr. As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder or all the above? No matter what you choose, we offer a work life that works for you, including: Immediate medical, dental, and prescription drug coverage Flexible family care, parental leave, new parent ramp-up programs, subsidized back-up child care and more Vehicle discount program for employees and family members, and management leases Tuition assistance Established and active employee resource groups Paid time off for individual and team community service A generous schedule of paid holidays, including the week between Christmas and New Year's Day Paid time off and the option to purchase additional vacation time. https://fordcareers.co/GSR-HTHD Verification of employment eligibility will be required at the time of hire.

Requirements

• Master's degree or foreign equivalent in Electronic Engineering, Data Analytics or related field and 4 years of experience in the job offered or related occupation.
• 4 years of experience with each of the following skills is required: 1. Applying Python (including Pandas, SciPy, Scikit-learn, NLTK, Keras, TensorFlow, and Statsmodels) as the primary language for data manipulation, statistical modeling, and developing machine/deep learning solutions using large-scale datasets from automotive manufacturing processes, vehicle telematics, quality control systems, or supply chain operations.
• Creating, developing and implementing Machine Learning & Deep Learning models to solve critical problems specific to automobile manufacturing, including predictive maintenance for factory equipment or vehicles, predicting production quality issues, optimizing assembly line efficiency, or analyzing complex sensor data from production or vehicle systems.
• Utilizing SQL for data mining to query and extract data from large relational databases containing manufacturing data, supply chain information, warranty claims data, or vehicle performance logs to support analysis and modeling activities.
• Employing statistical methods, including Regression analysis, Bayesian analysis, and ANOVA, to analyze manufacturing process variability, quality control metrics, engineering test outcomes, and operational data, providing statistical insights for production optimization and decision-making.
• Utilizing Cloud computing platforms including AWS and GCP, or scalable storage, processing, and analysis of large-scale automotive datasets (vehicle sensor data streams and production logs) and deploying data science solutions within a manufacturing or related operational context.
• Developing and evaluating A/B and multivariate tests to assess the impact of changes to manufacturing processes, internal systems (logistics and quality checks), or vehicle software features on key performance indicators within an automotive environment.
• 3 years of experience with each of the following skills is required: 1. Utilizing Natural Language Processing (NLP) techniques to analyze unstructured text data from sources critical to automotive operations, including manufacturing defect reports, warranty claims descriptions, maintenance logs, or customer feedback related to vehicles or production issues.

Responsibilities

• Utilizing Regression and Machine Learning Model Development for site traffic analysis.
• Utilizing Natural Language Processing, linear and logistic regression, decision trees, gradient boosting, and feature importance models.
• Designing multivariate experiments to measure site KPIs, such as conversion metrics.
• Performing post-test hypothesis testing.
• Applying ANOVA, Bayesian statistical analysis, regression principles, and statistical techniques for data analysis.
• Providing actionable business insights and decision support for site updates based on statistical analysis.
• Building, testing, implementing and analyzing A/B and multivariate testing programs.
• Communicating statistical and technical topics to non-technical business partners.
• Utilizing Python (Pandas, SciPi, ScikitLearn, NLTK, Keras, Tensorflow, and Statsmodels), and R.
• Utilizing SQL for data mining, including writing database queries for performance efficiency, including utilizing table indices and implementing database techniques to reduce cardinality, create tables, and partition data.

Benefits

• Immediate medical, dental, and prescription drug coverage
• Flexible family care, parental leave, new parent ramp-up programs, subsidized back-up child care and more
• Vehicle discount program for employees and family members, and management leases
• Tuition assistance
• Established and active employee resource groups
• Paid time off for individual and team community service
• A generous schedule of paid holidays, including the week between Christmas and New Year's Day
• Paid time off and the option to purchase additional vacation time

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level