Data Scientist I & II

Under general supervision, advances' broad capabilities to use and deploy cutting edge data science and machine learning tools and methods in projects, platforms and products. Anchors current best practices by supporting the design and build of reusable data science assets. Simultaneously works to keep on the bleeding edge by understanding the very latest and most sophisticated methods and tools for grappling with extremely large scale and complex problems.

• Applies descriptive, diagnostic, predictive, prescriptive and ensemble modeling, statistical techniques, and use of database tools and/or other approaches in quantitative analysis of complex business situations.
• Provides recommendations to moderately complex issues through knowledge of data scientific methods and machine learning / data engineering practices.
• Works in tandem with data scientists in peer positions

Title: Data Scientist I

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 robust, end-to-end pipelines and systems essential for their deployment. This includes proficiently leveraging APIs for data interaction 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 Azure and / or Google Cloud Platform (GCP) ecosystems.

Responsibilities

• Develop and implement predictive and descriptive analytics on structured and unstructured data, encompassing classification, regression, clustering, and hypothesis testing.
• Construct, test, and maintain robust end-to-end data ingestion and ETL/ELT pipelines from diverse sources (APIs, files, streaming), proficiently integrating and manipulating data via various APIs across the Google Cloud stack, including Pub/Sub and Dataflow.
• Craft scalable data models and transformations using SQL/Python, leveraging Databricks or BigQuery for optimal performance and data integrity.
• Design and create intuitive dashboards and visualizations that communicate complex metrics and insights clearly to stakeholders.
• Drive data quality and consistency initiatives, reconciling information from disparate sources.
• Actively participate in code reviews, enforce version control, and apply CI/CD and MLOps practices for seamless model deployment, with opportunities to explore Generative AI implementations.
• Collaborate with business partners and subject matter experts to translate complex questions into clear analytical insights and present findings effectively.
• Cultivate deep domain expertise in FedEx data and tools, taking direction from senior team members and contributing to knowledge sharing.
• Become fluent in working with and understanding the intricacies of FedEx's data landscape.

Minimum qualifications

• Bachelor's degree in data science, computer science, statistics, applied mathematics, industrial engineering, or a closely related quantitative field.
• 0-2 years of relevant experience (internships, academic projects, or co-ops are valued).
• Strong communication skills, an innate eagerness to learn, and a proactive problem-solving mindset.

Required technical skills

• Proficiency in SQL, Python, and/or R.
• Foundational knowledge of machine learning libraries (scikit-learn, XGBoost, TensorFlow, or PyTorch).
• Hands-on experience with Azure (e.g., Data Factory, Synapse, Databricks, Blob Storage) and / or Google Cloud Platform (GCP) and its core analytics/ML services (BigQuery, Vertex AI, Dataflow, Pub/Sub).
• Demonstrated ability to leverage various APIs for data manipulation and integration.
• Experience with at least one data visualization tool or package (e.g., Tableau, Power BI, Spotfire, Shiny, Plotly, Matplotlib, Seaborn).
• Solid understanding of ETL concepts, relational databases (e.g., Teradata, Oracle), and working with large-scale datasets.
• Proficiency with version control (git) and familiarity with MLOps/DevOps principles (CI/CD, model tracking, deployment workflows).

Preferred skills

• Academic or project experience demonstrating applied statistics, linear algebra, and probability.
• Exposure to distributed data processing frameworks (e.g., Apache Beam/Dataflow) or real-time streaming data architectures.
• Familiarity with Generative AI concepts or relevant tools (e.g., Vertex AI Gen AI Studio).
• Internship or project experience in transportation, logistics, or another relevant industry.

Additional Job Description

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.

Title: Data Scientist II

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 full power of the Azure and / or Google Cloud Platform (GCP) ecosystems - you will lead critical projects, mentor junior team members, and drive measurable business value in collaboration with product, engineering, and business stakeholders.

Responsibilities

• 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.
• Pioneer the design, development, and deployment of Generative AI solutions, capitalizing on Vertex AI's Gen AI capabilities and foundational models to unlock transformative business value.
• Construct and maintain highly reliable, scalable data ingestion and ETL/ELT pipelines for both batch and streaming sources using services like Azure Event Hubs or Azure IoT Hub and Azure Stream Analytics, GCP Dataflow, Pub/Sub, and BigQuery.
• Expertly design, integrate, and leverage APIs for seamless data flow and system interaction.
• Implement advanced MLOps and CI/CD strategies for models and pipelines, encompassing automated testing, deployment pipelines, model registry/tracking, robust rollback mechanisms, and comprehensive monitoring and alerting.
• Design and optimize sophisticated data architectures for analytics and ML workloads, including BigQuery schema design, partitioning/clustering strategies, and query optimization.
• Establish and enforce high standards for data quality, lineage, governance, and security (e.g., PII handling, RBAC, secrets management).
• Develop compelling dashboards and visualizations to translate complex insights into clear business actions and quantifiable KPIs.
• Strategically collaborate with engineering, data science, and business stakeholders to prioritize initiatives, design rigorous experiments (A/B tests), and drive successful implementations.
• Mentor and technically guide junior data scientists and analysts, actively contributing to team best practices, documentation, and knowledge sharing.
• Provide expert-level troubleshooting for production incidents, conducting thorough root cause analysis and implementing durable solutions.
• Cultivate deep domain expertise in FedEx data and business operations.

Minimum qualifications

• Bachelor's degree in data science, computer science, statistics, applied mathematics, operations research, or a related quantitative field. Master's degree preferred.
• 3-5 years of relevant industry experience building and deploying end-to-end analytics or ML systems; or equivalent experience with progressively increasing responsibility.
• Exceptional communication and stakeholder management skills, with a proven ability to translate complex technical output into clear business impact.

Required technical skills

• Expert proficiency in SQL, Python, and R.
• Extensive experience with leading ML frameworks (scikit-learn, XGBoost, TensorFlow, or PyTorch) and a proven track record of deploying them into production environments.
• Demonstrated expertise in developing and deploying solutions utilizing Generative AI models and platforms (e.g., large language models, prompt engineering).
• Deep, hands-on architectural and implementation experience with Azure (e.g., Data Factory, Synapse, Databricks, Blob Storage) and /or Google Cloud Platform (GCP) for end-to-end data and ML pipelines, including BigQuery, Dataflow, Vertex AI, Cloud Composer, and Pub/Sub.
• Mastery in designing, building, and leveraging APIs for robust data ingestion, integration, and exposing ML services.
• Extensive experience with data platforms / databases (BigQuery, Teradata, Oracle, Postgres) and engineering robust ETL/ELT jobs.
• Proficiency in developing advanced dashboards/visualizations (e.g., Tableau, Power BI, Spotfire, or visualization libraries like Plotly/Matplotlib/Seaborn).
• Expertise in performance tuning, query optimization, and the design of efficient, scalable data models.

Preferred qualifications

• Advanced experience with native Azure / GCP streaming technologies or event-driven architectures.
• Proficiency with monitoring, observability, and data-quality tools (e.g., Great Expectations, Prometheus, Grafana, or similar).
• Proven experience with prompt engineering, RAG architectures, or fine-tuning foundational models.
• Domain expertise in logistics, transportation, finance, healthcare, or other industry-relevant contexts.
• Experience mentoring or leading small project teams.

Core competencies

• Strong problem-solving acumen, advanced statistical reasoning, and pragmatic applied machine learning judgment, including for Generative AI applications.
• Pragmatic engineering mindset: consistently produce reliable, maintainable solutions, take full ownership of the deployment lifecycle, and effectively trade off speed versus robustness.
• Ability to work independently and collaboratively across distributed teams, fostering a strong team environment.
• Comfortable with ambiguity; able to strategically prioritize and deliver under tight timelines with high quality.

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.

Preferred Qualifications:

Pay Transparency: This compensation range is provided as a reasonable estimate of the current starting salary range for this role across all potential locations. If this opportunity includes multiple job levels, the range is a reasonable estimate of the current starting salary for the lowest level to the current starting salary of the highest level. Actual starting pay would be determined by experience relative to the job, market level, pay at the location for this job and other job-related factors. An employee may be eligible for additional pay, premiums, or bonus potential. The Company offers eligible employees health, vision, and dental insurance, retirement plans, and tuition reimbursement

Pay:

Data Scientist I: 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: 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

Additional Details:

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

• Know Your Rights
• 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.