Data Scientist I and II (GCP & AI Engineer)

FedEx is seeking early-career and experienced Data Scientists to ignite their careers and lead innovation in data solutions. The roles involve designing, building, and deploying data models and analytics solutions, while collaborating with teams to drive business value and optimize product development strategies.

What you'll do:

• Develop and implement predictive and descriptive analytics on structured and unstructured data, encompassing classification, regression, clustering, and hypothesis testing
• Clean, curate, and transform raw data from existing tables and systems using SQL and Python to prepare high-quality datasets for model training and evaluation
• Write efficient SQL queries and Python scripts to extract, manipulate, and explore data housed within BigQuery and Cloud Storage (GCS)
• Design and create intuitive dashboards and visualizations in Looker and Looker Studio to communicate metrics and insights clearly to team members and stakeholders
• Actively participate in code reviews, enforce version control (Git), and apply foundational CI/CD and MLOps practices (such as model tracking) for seamless deployment
• Explore Generative AI concepts and foundational models using Vertex AI Generative AI Studio to identify potential business use cases
• Collaborate with business partners to translate operational questions into analytical insights, while cultivating deep domain expertise in FedEx data systems and business operations
• Lead the complete lifecycle of analytics and ML projects, from problem definition and data discovery to feature engineering, model development, validation, deployment, and continuous monitoring
• Architect, develop, and productionize advanced predictive and prescriptive models (classification, regression, clustering, time series, optimization), effectively serving them via Vertex AI Pipelines and Endpoints
• Design, develop, and deploy practical Generative AI solutions (e.g., Retrieval-Augmented Generation/RAG architectures, prompt design) using Vertex AI Gen AI capabilities
• Expertly design, build, and integrate RESTful APIs (e.g., FastAPI, Flask) for seamless model serving and microservice-based ML system integration
• Implement advanced MLOps and CI/CD strategies for models and serving pipelines, encompassing automated testing, deployment pipelines, model registry/tracking, and comprehensive drift and performance monitoring

What they're looking for:

• Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, Industrial Engineering, or a closely related quantitative field
• 0–3 years of relevant experience (internships, academic projects, or co-ops are highly valued)
• Strong communication skills, an innate eagerness to learn, and a proactive, collaborative problem-solving mindset
• Proficiency in SQL and Python
• Foundational knowledge of machine learning libraries (scikit-learn, XGBoost, TensorFlow, or PyTorch)
• Hands-on exposure to Google Cloud Platform (GCP), specifically BigQuery, Vertex AI, and Cloud Storage (GCS) for data retrieval and modeling
• Demonstrated ability to interact with and leverage RESTful APIs for consuming model inputs and integration
• Experience with at least one visualization tool (e.g., Looker, Looker Studio, Tableau) or Python plotting libraries (Matplotlib, Seaborn)
• Foundational understanding of Git, relational database concepts, and basic MLOps/DevOps workflows
• Expert proficiency in Python and SQL
• Extensive experience with leading ML frameworks (scikit-learn, XGBoost, TensorFlow, or PyTorch) and a proven track record of deploying them to production environments
• Hands-on experience developing solutions utilizing GenAI models (e.g., working with LLMs, prompt engineering, and utilizing Vertex AI Model Garden)

Benefits:

• This position is eligible for remote work and may be located anywhere within the United States excluding AK, HI and U.S. territories, however if you live within the 50 miles radius of a campus you will be required to work at a FedEx campus location several times per week.