AI/ML Data Scientist, GPSSC

• Work with existing business partners to identify opportunities for AI/ML solutions that enhance processes and improve team-member efficiency
• Train machine learning models to solve complex business problems
• Prototype AI solutions, including Generative AI
• Develop Agentic AI solutions to streamline business processes
• Enhance existing model solutions as business and technology evolve
• Provide guidance on business problems using statistical methods
• Craft ad-hoc reports sharing findings and recommendations with business partners
• Build statistical models depicting company-wide trends
• Test and validate datasets
• Refine storytelling skills to convey ideas and results to leadership, customers, and stakeholders
• Work with customers to understand challenges and needs
• Work with ML Ops in a cloud environment
• Develop proofs of concept for generative AI and Agentic AI solutions

Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
• 5+ years of experience in machine learning, engineering, data science, or a related field
• Experience with Python, R, Java, PySpark, PyTorch, TensorFlow, Scikit-learn, LangChain, and SQL
• Experience with Large Language Models (LLMs), Generative AI, RAG, deep learning, reinforcement learning, NLP, SVM, XGBoost, Random Forest, Decision Trees, and clustering
• Experience with Databricks, Hadoop, data pipelines, data preprocessing, and feature engineering
• Preferred experience with Microsoft Azure, including Data Lake, Machine Learning, and Databricks
• Nice to have AWS or Google Cloud Platform experience
• Experience with MLflow, model monitoring and versioning, Docker, Kubernetes, GitHub, and Jira
• Experience with Tableau, PowerBI, Pandas, and NumPy
• Proven track record delivering AI/ML solutions to customers that achieve continued usage and drive value
• Excellent communication and collaboration skills
• Strong problem-solving mindset and proactive attitude toward learning and self-improvement
• Preferred: deep knowledge of GM’s Data Ecosystem, GM’s Cloud Technology Stack for Data Science, and Global Product Safety’s SFI Process
• Preferred: extensive NLP solutions experience from business problem statement through deployment and ongoing optimization
• Preferred: expertise with LLM solutions through cloud deployment that provided significant incremental business value
• Preferred: experience developing and deploying generative AI solutions into production with significant incremental business value

Core Competencies

Demonstrates expertise in developing and deploying AI/ML solutions, including Generative AI and Agentic AI, while leveraging statistical methods and cloud technologies to enhance business processes. Strong ability to communicate findings and recommendations effectively to stakeholders and leadership.

Highest-signal resume keywords

• Machine Learning
• Generative AI
• Python
• Statistical Modeling
• Cloud Environment

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Data Science
• Statistical Modeling
• Feature Engineering
• Natural Language Processing
• Deep Learning
• Reinforcement Learning
• Data Preprocessing
• Model Monitoring
• Data Pipelines

Soft Skills

• Excellent Communication
• Collaboration
• Problem-Solving Mindset
• Proactive Attitude
• Storytelling Skills

Industry Keywords

• AI Solutions
• ML Ops
• Large Language Models
• Generative AI Solutions
• Data Ecosystem
• Cloud Technology Stack
• Global Product Safety
• NLP Solutions
• Incremental Business Value
• Business Problem Statement

Tools & Technologies

• Python
• R
• Java
• PySpark
• PyTorch
• TensorFlow
• SQL
• Databricks
• Microsoft Azure
• MLflow