Data Scientist

Ford Motor • Dearborn, MI

2h • $128,710 - $182,339 • Hybrid

About The Position

At Ford Motor Company, we believe freedom of movement drives human progress. We also believe in providing you with the freedom to define and realize your dreams. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career potential as you help us define tomorrow’s transportation. Do you believe data tells the real story? We do! Redefining mobility requires quality data, metrics, and analytics, as well as insightful interpreters and analysts. That's where Global Data Insight & Analytics makes an impact. We advise leadership on business conditions, customer needs and the competitive landscape. With our support, key decision makers can act in meaningful, positive ways. Join us and use your data expertise and analytical skills to drive evidence-based, timely decision making.

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.
• 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.

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