Data Scientist - Sr. Data Scientist

Full Time
Township of Moon, PA 15108
Posted
Job description

Employs scientific methods and data-discovery tools to find new patterns, insights and relationships in big data; extracts meaningful information from multiple large data sets; develops solutions that quickly and visually communicate results; acts as a subject matter expert in data structure and storage; collaborates closely with IT departments.

Essential Functions

Performs both qualitative analysis (e.g., content analysis, phenomenology, hypothesis testing) and quantitative analysis (e.g., clustering regression, pattern recognition, descriptive and inferential statistics) on large data sets to understand trends and relationships between variables to gain predictive insights. • Designs and implements experiments to answer targeted questions and solves known issues by actively engaging with business partners to understand key business challenges. • Leads investigations into multiple streams of data to solve complex business problems. • Designs and implements reporting dashboards utilizing established data warehouse structures that track and visually communicate key business metrics and provide actionable insights. • Writes and interprets complex queries to solve business problems; designs and reviews algorithms based on examples to provide analysis and insights into trends used for predictability; streamlines and automates existing reporting and analysis inventory, and new project success metrics to exceed FedEx Quality standards through application of Quality Drive Management (QDM) principles and tools. • 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.

Minimum Education

  • Degree in Data Science or similar field with emphasis on Machine Learning, Predictive Analytics, Advanced Analytics, Stream Processing, Visualizations required. Master’s preferred.

Minimum Experience

  • Demonstration in solving analytics problems through the application of data science techniques in academic or workplace examples required.

Required Skills, Abilities and / or Licensure

• Proficient with MS office applications. • Expert level with SQL (Structured Query Language). • Experience with Teradata and Oracle relational database platforms is desired. • Experience data modeling, ETL (Extract-Transform-Load) concepts, query performance tuning and testing is a plus. • Experience with large datasets, Map-Reduce architecture frameworks such as Pig and Scalding, statistical software such as R, and scripting languages like Python and Ruby is a plus. • Experience with visualization tools such as Tableau or Spotfire is a plus. • Ability to read, analyze, and interpret common technical journals, reports, and related documents. • Ability to effectively present information to management, end users, co-workers, or vendors. • Ability to work with mathematical concepts such as probability. • Ability to apply concepts such as percentages, ratios, proportions and ranking to create practical situations. • Ability to define problems, collect data, establish facts, and draw valid conclusions • Requires strong analytical and problem solving skills. • Ability to perform complex tasks with limited direction

Other Job Description Information

This is a corporate position that is domiciled in Pittsburgh, PA. Remote locations will be considered with appropriate approvals.

% of Travel for the Position: <25%
Address: 1000 FedEx Drive
City: Moon Township
State: Pennsylvania
Zip Code: 15108
Domicile Location: FXG-US/USA/P090/PGH - FedEx Ground
Auto req ID: 389870BR
Position Type: Full time
Employee Type: Exempt

EEO Statement

FedEx Ground is an equal opportunity / affirmative action employer (Minorities/Females/Disability/Veterans) committed to a diverse workforce

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