Data Scientist I and II (GCP & AI Engineer)

Description

Data Scientist I (GCP & AI Engineer)

Overview

Ignite your career as an early-career Data Scientist, playing a pivotal role in designing, building, and deploying innovative solutions that deliver tangible business value. We are seeking individuals who are profoundly passionate not only about developing cutting-edge models but also about constructing the feature preparation systems and deployment workflows essential for their success. This includes learning to leverage APIs for model integration and actively exploring the transformative potential of Generative AI. You will contribute to our mission within a collaborative, mentorship-driven environment, working hands-on with the Google Cloud Platform (GCP) ecosystem under the guidance of senior team members.

Works as part of a team to employ scientific methods and data-discovery tools to find new patterns, insights, and relationships in big data; extract meaningful information from multiple large data sets and develop solutions that quickly and visually communicate results. Participates and collaborates in discussions across business and IT teams to understand data product needs. Analyzes data from various databases to drive optimization and improvement of product development and business strategies. Independently works on analyzing and interpreting data to identify trends, insights, and logical data driven solutions for business problems. Develops analytical models and algorithms which apply data to identify business improvement insights and inform the development of processes and tools (e.g. dashboards, other visualizations) for monitoring, analyzing, and evaluating analytical model performance. Ensures accuracy and quality of data, including reconciliation from disparate sources. Partners with other team members to collaborate with stakeholders, customers, and other functional teams. Works alongside other data scientists to understand business questions, identify opportunities to leverage data to drive business solutions, implement models, and monitor outcomes.

Responsibilities

• Foundational Modeling: Develop and implement predictive and descriptive analytics on structured and unstructured data, encompassing classification, regression, clustering, and hypothesis testing.
• Data Preparation & Feature Engineering: 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.
• Data Retrieval & Manipulation: Write efficient SQL queries and Python scripts to extract, manipulate, and explore data housed within BigQuery and Cloud Storage (GCS).
• Business Intelligence: Design and create intuitive dashboards and visualizations in Looker and Looker Studio to communicate metrics and insights clearly to team members and stakeholders.
• MLOps & Version Control: Actively participate in code reviews, enforce version control (Git), and apply foundational CI/CD and MLOps practices (such as model tracking) for seamless deployment.
• GenAI Exploration: Explore Generative AI concepts and foundational models using Vertex AI Generative AI Studio to identify potential business use cases.
• Collaboration & Domain Growth: Collaborate with business partners to translate operational questions into analytical insights, while cultivating deep domain expertise in FedEx data systems and business operations.

Minimum Qualifications

• Education: Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, Industrial Engineering, or a closely related quantitative field.
• Experience: 0–3 years of relevant experience (internships, academic projects, or co-ops are highly valued).
• Communication: Strong communication skills, an innate eagerness to learn, and a proactive, collaborative problem-solving mindset.

Required Technical Skills

• Core Languages: Proficiency in SQL and Python.
• ML Frameworks: Foundational knowledge of machine learning libraries (scikit-learn, XGBoost, TensorFlow, or PyTorch).
• GCP Analytics Services: Hands-on exposure to Google Cloud Platform (GCP), specifically BigQuery, Vertex AI, and Cloud Storage (GCS) for data retrieval and modeling.
• API Integration: Demonstrated ability to interact with and leverage RESTful APIs for consuming model inputs and integration.
• Data Visualization: Experience with at least one visualization tool (e.g., Looker, Looker Studio, Tableau) or Python plotting libraries (Matplotlib, Seaborn).
• Version Control & DevOps: Foundational understanding of Git, relational database concepts, and basic MLOps/DevOps workflows.

Preferred Qualifications

• GCP Fundamentals: Familiarity with GCP cloud environments (e.g., passing the Google Cloud Digital Leader or Associate Cloud Engineer exam is a plus).
• Advanced GenAI: Academic or personal project experience with Large Language Models (LLMs) or prompt engineering.
• Industry Context: Internship or project experience in transportation, logistics, or supply chain.

USA: $5,364.26/mo - $11,801.37/mo, CO: $5,364.26/mo - $11,309.65/mo, CA: $5,662.27/mo - $9,476.86/mo, NJ: $5,662.27/mo - $9,059.63/mo, OH & VT: $5,662.27/mo - $9,342.75/mo, MN: $5,662.27/mo - $10,817.92/mo, IL & NV: $5,662.27/mo - $11,309.65/mo, MD, NY & WA: $5,662.27/mo - $11,801.37/mo, MA: $5,960.29/mo - $11,801.37/mo, RI: $6,556.32/mo - $10,817.92/mo, CT: $6,556.32/mo - $11,309.65/mo, DC & HI: $6,854.33/mo - $11,309.65/mo, NYC: $6,854.33/mo - $11,801.37/mo

Data Scientist II (GCP & AI Engineer)

Overview

Elevate your career as a Data Scientist II and become a cornerstone of our innovation. We are seeking a highly skilled and experienced Data Scientist who deeply understands that impact comes not just from building cutting-edge models, but from owning their entire lifecycle from conception to production-ready deployment. If you are passionate about architecting, developing, and operationalizing robust, end-to-end machine learning and analytics solutions, integrating seamlessly with diverse APIs, and championing the adoption of Generative AI, then this role is for you. Leveraging the power of the Google Cloud Platform (GCP) ecosystem, you will lead critical projects, mentor junior team members, and drive measurable business value in collaboration with product, engineering, and business stakeholders.

Responsibilities

• End-to-End ML Ownership: 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.
• Vertex AI Development: Architect, develop, and productionize advanced predictive and prescriptive models (classification, regression, clustering, time series, optimization), effectively serving them via Vertex AI Pipelines and Endpoints.
• Generative AI Implementation: Design, develop, and deploy practical Generative AI solutions (e.g., Retrieval-Augmented Generation/RAG architectures, prompt design) using Vertex AI Gen AI capabilities.
• Robust Feature Engineering: Design and implement robust feature stores and transformation logic to feed training and real-time inference workflows, ensuring model input consistency and drift mitigation.
• API Design & Deployment: Expertly design, build, and integrate RESTful APIs (e.g., FastAPI, Flask) for seamless model serving and microservice-based ML system integration.
• MLOps & CI/CD Practices: 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.
• BigQuery Query Optimization: Optimize data models, analytical views, and SQL queries to support efficient, low-latency machine learning training and inference workloads.
• Reporting & Visualizations: Develop compelling, interactive dashboards using Looker/Looker Studio to translate complex insights into clear business actions and quantifiable KPIs.
• Mentorship & Collaboration: Mentor and technically guide junior data scientists and analysts, actively contributing to team-wide best practices, documentation, and troubleshooting production incidents.
• Domain Alignment: Cultivate deep domain expertise in FedEx data and business operations to align ML efforts with immediate team goals.

Required Technical Skills

• Core Languages: Expert proficiency in Python and SQL.
• ML Frameworks: Extensive experience with leading ML frameworks (scikit-learn, XGBoost, TensorFlow, or PyTorch) and a proven track record of deploying them to production environments.
• Generative AI Platforms: Hands-on experience developing solutions utilizing GenAI models (e.g., working with LLMs, prompt engineering, and utilizing Vertex AI Model Garden).
• GCP Ecosystem: Deep hands-on experience with Google Cloud Platform (GCP) for end-to-end ML, specifically BigQuery, Vertex AI, Vertex AI Feature Store, and Cloud Storage (GCS).
• API Architecture: Proficiency in designing, building, and securing APIs (e.g., FastAPI, Flask) to expose ML microservices.
• Performance Tuning: Expertise in performance tuning, SQL query optimization, and the design of efficient, scalable models for ML data preparation.

Preferred Qualifications

• GCP Certifications: Professional Google Cloud Machine Learning Engineer certification.
• Observability & Data Quality: Experience with monitoring, observability, and automated data-quality tools (e.g., Great Expectations, GCP Cloud Monitoring, Cloud Logging for ML model performance).
• Logistics Domain: Domain expertise in logistics, transportation, supply chain, or related industries.

Minimum Education:

Master’s degree (or equivalent) in Computer Science, Operations Research, Statistics, Applied Mathematics, or a related quantitative field.

Minimum Experience:

At least two (2) years of professional experience applying data science (e.g., machine learning, artificial intelligence, statistical analysis), operations research (e.g., optimization, algorithms, mathematical modeling), and data analytics to reduce costs, enhance profitability, and improve customer experience. An advanced degree in a related field may be considered in lieu of some experience.

USA: $6,168.90/mo - $13,571.58/mo, CO: $6,168.90/mo - $13,006.09/mo, CA: $6,511.62/mo - $10,898.39/mo, NJ: $6,511.62/mo - $10,418.59/mo, OH & VT: $6,511.62/mo - $10,744.16/mo, MN: $6,511.62/mo - $12,440.61/mo, IL & NV: $6,511.62/mo - $13,006.09/mo, MD, NY & WA: $6,511.62/mo - $13,571.58/mo, MA: $6,854.33/mo - $13,571.58/mo, RI: $7,539.76/mo - $12,440.61/mo, CT: $7,539.76/mo - $13,006.09/mo, DC & HI: $7,882.48/mo - $13,006.09/mo, NYC: $7,882.48/mo - $13,571.58/mo

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.

Preferred Qualifications:  

Pay Transparency:   

Pay: 

Additional Details: 

FedEx Dataworks is an Equal Opportunity Employer including, Vets/Disability.

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• Pay Transparency

Dataworks does not discriminate against qualified individuals with disabilities in regard to job application procedures, hiring, and other terms and conditions of employment. Further, Dataworks is prepared to make reasonable accommodations for the known physical or mental limitations of an otherwise qualified applicant or employee to enable the applicant or employee to be considered for the desired position, to perform the essential functions of the position in question, or to enjoy equal benefits and privileges of employment as are enjoyed by other similarly situated employees without disabilities, unless the accommodation will impose an undue hardship. If a reasonable accommodation is needed, please contact DataworksTalentAcquisition@corp.ds.fedex.com.