Data Scientist

Federal Express Corporation

United States

United States

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À propos

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. Essential Functions Works as part of a team to perform advanced analytics, including predictive Machine Learning (classification and regression, supervised and unsupervised modeling), inferential statistics, hypothesis testing, and qualitative analysis on large data sets that include both structured and unstructured data to develop crucial business insights and communicate to the business in an understandable way. Work as part of a team to develop and deploy analytical and machine learning models (with general understanding of data engineering and ML Ops). 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). Designs and implements reporting dashboards and other visualizations that track and visually communicate key business metrics and provide actionable insights. Participates in design sessions to implement experiments to answer targeted questions and solves known issues by actively engaging with business partners to understand key business challenges. Learn and become fluent working with and understand FedEx data. Identifies internal and external information sources, builds effective working relationships with subject matter experts within FedEx and the external marketplace. Assists with knowledge transfer and training of business intelligence to the FedEx team as a subject matter expert; strongly influences the team by developing, institutionalizing and maintaining a data-driven analysis culture. Analyzes data from various databases to drive optimization and improvement of product development and business strategies. Ensures accuracy and quality of data, including reconciliation from disparate sources. Performs other duties as assigned. Minimum Education Bachelor's in data science, computer science, applied mathematics, data analytics, statistics, industrial engineering, or related quantitative field. Minimum Experience Zero (0) to three (3) years relevant experience required. Skills can be gained concurrently with education. Proficiency required in at least one programming language, such as (SQL, Python, R, Java, or similar language) and one visualization tool/package such as (Spotfire, Tableau, Power BI, ShinyApp, Plotly, Matplotlib, Seaborn or similar tool) required. Knowledge, Skills, and Abilities Proficient in at least one programming language, such as (SQL, Python, R, Java, etc.). Proficient in one visualization tools/packages, such as (Spotfire, Tableau, Power BI, ShinyApp, Plotly, Matplotlib, Seaborn). Exposure to relational database platforms, such as Teradata and Oracle. Experience in data mining, developing/implementing statistical models, machine learning models, algorithms, or visualizing data. Experience with statistical programming languages such as R, Python, SQL, and SAS required. Exposure to Machine Learning modeling, including scripting and Machine Learning libraries in R, Python, or similar. Exposure with Cloud platforms, including storage, querying, and advanced analytics (Azure, GCP, AWS). Understanding of statistics with exposure to linear algebra. Ability to define problems, collect data, establish facts, and draw valid conclusions. Ability to read, analyze, and interpret common technical journals, reports, and related documents. Exposure to data modeling, ETL (Extract-Transform-Load) concepts, query performance tuning and testing. Exposure to large datasets and the management of large data. Experience data modeling, ETL (Extract-Transform-Load) concepts, query performance tuning and testing is a plus. Experience with visualization tools such as Tableau or Spotfire is a plus. Ability to effectively present information to management, end users, co-workers, or vendors. Strong problem-solving skills. Strong written and verbal communication skills. Strong interpersonal skills. Ability to work on multiple projects and work as part of a team. Preferred Qualifications Master's or Ph.D. degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative field. Experience designing, developing, and deploying machine learning models on Google Cloud Platform (GCP) using Vertex AI, BigQuery ML, Cloud Storage, and related services. Experience with large-scale data processing, feature engineering, MLOps, and AI/ML model deployment using Python, SQL, Spark, and cloud-native technologies. 3+ years of hands-on experience developing machine learning, predictive analytics, or AI solutions in a cloud environment. Strong programming skills in Python and SQL with experience using Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Experience building and deploying machine learning models for forecasting, classification, anomaly detection, recommendation engines, or NLP use cases. Experience with MLOps practices, CI/CD pipelines, model monitoring, feature stores, and automated model deployment. Experience communicating analytical insights through dashboards and visualizations using Looker, Power BI, Tableau, or similar BI tools. Preferred Qualifications: Pay Transparency: Pay: Additional Details:
This is a hybrid position located in Memphis, TN. Candidates must live within 50 miles of the campus location. Employees will be required to work at the FedEx campus location several times per week. Posting closes on: 6/11/2026 at 4:00 PM CST/5:00 PM EST. For details on our comprehensive benefits, click
here
. Federal Express Corporation is an Equal Opportunity Employer including, Vets/Disability. Reasonable accommodations are available for qualified individuals with disabilities throughout the application process. Applicants who require reasonable accommodations in the application or hiring process should contact recruitmentsupport@fedex.com. Applicants have rights under Federal Employment Laws: Know Your Rights Pay Transparency Family and Medical Leave Act (FMLA) Employee Polygraph Protection Act E-Verify Program Participant: Federal Express Corporation participates in the Department of Homeland Security U.S. Citizenship and Immigration Services' E-Verify program (For U.S. applicants and employees only). Please click below to learn more about the E-Verify program: E-Verify Notice (bilingual) Right to Work Notice (English) / (Spanish)

United States

Compétences linguistiques

English

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