Data Scientist

In Global Data Insight & Analytics (GDI&A), we harness the power of data and artificial intelligence to navigate Ford Motor Company through the disruptiveness of the information age. We're a team of innovators who strive to realize the enterprise's goals, reveal hidden opportunities, and achieve data superiority.

We are looking for a seasoned Data Scientist with 3+ years of experience in AI/ML, preferably with some experience in Generative AI. You're a humble and collaborative individual who thrives in a fast-paced environment. You're passionate about developing and delivering data analytics and machine learning models that drive business impact.

Develop a strong understanding of business problems and translate them into practical AI, Generative AI, and machine-learning solutions.

Design, build, and maintain end-to-end AI/ML pipelines, from data ingestion and preprocessing through model development, evaluation, deployment, and monitoring.

Develop analytics and AI solutions, including classification, time-series forecasting, LLM applications, and retrieval-augmented generation (RAG).

Build LLM-powered applications using Python, applying prompt engineering and structured outputs to support reliable, task-appropriate results.

Develop RAG workflows, including document ingestion, chunking, embeddings, vector search, and integration of retrieved content into LLM responses.

Evaluate and validate machine-learning and LLM solutions using appropriate methods and metrics, such as precision, recall, F1, ROC-AUC, and RMSE.

Write clean, efficient, and well-documented Python code for data manipulation, feature engineering, model development, and AI application integration.

Use SQL to extract, transform, and prepare data from relational databases and other data sources.

Collaborate with data engineers and other partners to identify and assess data sources, support reliable data infrastructure, and turn data into actionable business outcomes.

Monitor and maintain deployed AI/ML solutions, addressing performance, reliability, quality, and model or response degradation.

Analyze complex datasets to identify trends, patterns, and insights that inform model development and business decisions.

Communicate technical concepts, evaluation results, and recommendations effectively to technical and non-technical stakeholders.

Take ownership of projects and deliver outcomes independently, seeking guidance when needed.

Contribute to a collaborative team environment and show respect for colleagues and their contributions.

Stay current with relevant developments in AI, machine learning, LLMs, and data science, and assess their potential value for business use.

Minimum Qualifications

• Master's degree (M.S.) in Data Science, Computer Science, Business Analytics, Machine Learning, Statistics, or a related quantitative field.
• 3+ years of experience in AI/ML, with proven experience developing and deploying machine learning models in a production environment.
• Strong proficiency in Python for data science and machine learning.
• Expertise in SQL for data querying, manipulation, and database interaction.
• Strong skills in data acquisition, algorithm design, and model development and refinement.
• Experience with big data technologies, cloud-based data platforms (e.g., GCP, AWS), and business intelligence tools (e.g., Power BI, Streamlit, Plotly Dash).
• Solid understanding of machine learning algorithms, statistical modeling, and data analysis techniques.
• Excellent oral, written, and interpersonal communication skills.

Preferred Qualifications

• Ph.D. in Data Science, Computer Science, Business Analytics, Machine Learning, Statistics, or a related quantitative field.
• 5+ years of experience in data science and analysis, including leadership or mentoring roles.
• Significant experience in Generative AI, including a strong understanding of ML frameworks, algorithms, and practical implementation.
• Experience in specialized areas such as Natural Language Processing (NLP), deep learning (e.g., TensorFlow, PyTorch), or recommendation systems.
• Experience with building and managing data pipelines, including familiarity with orchestration tools (e.g., Apache Airflow, Kubeflow) or DBT.
• Certifications in Google Cloud Platform (GCP) or other cloud platforms.
• Experience with agile development methodologies and version control systems (e.g., Git).
• A record of publications or presentations in recognized journals or conferences.