We are seeking a Staff Engineer specializing in Data Science with a strong background in the automotive domain. This role requires 9 to 13 years of professional experience, focusing on applying data-driven solutions to industry-specific challenges, particularly within the context of Ford's operations.

Expertise in Python, including libraries like Pandas, NumPy, and Scikit-learn, is fundamental for data manipulation and building sophisticated machine learning models. Proficiency in SQL is also critical for effectively managing, querying, and optimizing large datasets.

A solid understanding of Natural Language Processing (NLP) is vital for analyzing human language data, while a strong foundation in Machine Learning (ML) and Artificial Intelligence (AI) is necessary for implementing advanced algorithms and predictive models. Familiarity with data governance best practices and the ethical use of AI is expected.

Develop and implement data-driven solutions relevant to the automotive domain, leveraging advanced data science techniques.

Utilize Python and its associated libraries for data manipulation, analysis, and machine learning model development.

Manage and query large datasets effectively using SQL to ensure data integrity and optimize performance.

Extract meaningful insights from data through comprehensive analysis to support informed decision-making.

Apply NLP techniques to analyze and interpret textual data, enhancing user experience and product capabilities.

Implement advanced ML and AI algorithms to drive innovation and create predictive models.

Adhere to best practices in data governance and ensure the ethical application of AI technologies.

A minimum of 9 to 13 years of professional experience in Data Science, with a focus on the automotive industry.

Advanced proficiency in Python, including hands-on experience with Pandas, NumPy, and Scikit-learn.

Expertise in SQL for database management and complex querying.

Substantial experience in data analysis methodologies and extracting actionable insights.

A solid understanding of Natural Language Processing (NLP).

Proficiency in Machine Learning (ML) and Artificial Intelligence (AI) for building advanced models.

Familiarity with data governance principles and ethical AI practices is expected.

A Master of Science (M.Sc.) in Data Science or a Postgraduate Diploma in Data Science is required.

Certifications such as Certified Data Scientist or Certified Analytics Professional are preferred.

Experience with LLMOps practices and knowledge of Git version control systems are considered advantageous.