Data Scientist at Ford Global Career Site

Dearborn, Michigan, United States -

Full Time

Start Date

Immediate

Expiry Date

14 Apr, 26

Salary

0.0

Posted On

14 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Cleaning, Exploratory Data Analysis, Statistical Modeling, Machine Learning, Model Deployment, Business Translation, Python, R, Data Manipulation, SQL, Cloud Computing, Google Cloud Platform, TensorFlow, PyTorch, Auto Industry

Industry

Motor Vehicle Manufacturing

Description

Acquire, clean, and process messy, real-world data from various sources to prepare it for analysis and modeling. Perform rigorous Exploratory Data Analysis (EDA) to understand data characteristics, identify patterns, uncover hidden insights, and formulate hypotheses. Translate complex business questions and challenges into well-defined data science problems and analytical tasks. Develop, train, and evaluate statistical and machine learning models to address specific business needs (e.g., prediction, classification, clustering, forecasting). Collaborate closely with engineering and product teams to deploy models into production environments, ensuring scalability, reliability, and performance monitoring. Communicate findings and model results clearly and effectively to technical and non-technical stakeholders, translating complex data analysis results into actionable business recommendations and solutions. Iterate on models and approaches based on performance feedback and evolving business requirements. Stay up-to-date with the latest advancements in data science, machine learning, and relevant technologies. Established and active employee resource groups Master's degree in Statistics, Mathematics, Computer Science, or a closely related quantitative field. Demonstrated ability to deal with and process data from real-world sources. Experience performing Exploratory Data Analysis (EDA). Experience with model development (statistical modeling, machine learning). Familiarity with the process of deploying models into production or working alongside teams that do. Proven ability to translate business questions into data-driven problems. Ability to translate data analysis results and model insights into clear, business-oriented solutions. Proficiency in at least one major programming language used in data science (e.g., Python, R). Experience with data manipulation and analysis libraries/tools (e.g., Pandas, SQL). PhD in Statistics, Mathematics, Computer Science, or a closely related quantitative field. -Experience working with cloud computing platforms, particularly Google Cloud Platform (GCP). Experience with specific machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Experience in Auto Industry

Responsibilities

Acquire, clean, and process messy data for analysis and modeling. Develop and evaluate statistical and machine learning models to address business needs and communicate findings to stakeholders.