FedEx
Sr Marketing Data Scientist
FedEx - Plano, Texas, us, 75086
Work at FedEx
Overview
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Overview
Job Description
Under moderate supervision, provides expertise at the enterprise level related to large datasets, enterprise analytics, statistical modeling, and AI/ML initiatives. Utilizes expert knowledge of customer, consumer, economic, demand, market, competition, and internal process data to develop analytical solutions for well-defined, lower-complexity business problems. Develops and implements solutions from concept to production and communicates results to diverse audiences. Provides thought leadership and leads cross-functional teams in descriptive, diagnostic, predictive, and prescriptive modeling, advanced statistical analysis, and other quantitative analyses of complex business scenarios. Uses current and emerging technologies to evaluate trends and develop actionable insights and recommendations for business partners and management. Makes use of data analysis, statistical and quantitative modeling, and fact-based management to inform decision-making. Leads cross-functional projects, prepares, and presents findings to management, and provides ongoing consultation. Manages multiple assignments concurrently and mentors less experienced staff. Qualifications Master's degree in data science, analytics, business, mathematics, economics, computer science, or related quantitative fields such as engineering or operations research. At least 2 years of experience in an analytical, quantitative, or technical role in business, mathematics, economics, computer science, or related fields. At least 1 year of experience or coursework in decision support tools, analytical/modeling languages (e.g., Python, R, SAS, SQL), and data visualization tools (e.g., Tableau, PowerBI, Spotfire). Knowledge, Skills, and Abilities Strong problem-solving, analytical, and communication skills. Advanced degrees may offset experience requirements. Preferred Qualifications Experience with analytics, machine learning, and deep learning on cloud platforms like Azure, focusing on time series forecasting, customer insights, and market analysis using Python, SQL, or PySpark. Knowledge of Data Engineering, Cloud Platforms, and MLOps to facilitate communication across multi-functional teams.
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Under moderate supervision, provides expertise at the enterprise level related to large datasets, enterprise analytics, statistical modeling, and AI/ML initiatives. Utilizes expert knowledge of customer, consumer, economic, demand, market, competition, and internal process data to develop analytical solutions for well-defined, lower-complexity business problems. Develops and implements solutions from concept to production and communicates results to diverse audiences. Provides thought leadership and leads cross-functional teams in descriptive, diagnostic, predictive, and prescriptive modeling, advanced statistical analysis, and other quantitative analyses of complex business scenarios. Uses current and emerging technologies to evaluate trends and develop actionable insights and recommendations for business partners and management. Makes use of data analysis, statistical and quantitative modeling, and fact-based management to inform decision-making. Leads cross-functional projects, prepares, and presents findings to management, and provides ongoing consultation. Manages multiple assignments concurrently and mentors less experienced staff. Qualifications Master's degree in data science, analytics, business, mathematics, economics, computer science, or related quantitative fields such as engineering or operations research. At least 2 years of experience in an analytical, quantitative, or technical role in business, mathematics, economics, computer science, or related fields. At least 1 year of experience or coursework in decision support tools, analytical/modeling languages (e.g., Python, R, SAS, SQL), and data visualization tools (e.g., Tableau, PowerBI, Spotfire). Knowledge, Skills, and Abilities Strong problem-solving, analytical, and communication skills. Advanced degrees may offset experience requirements. Preferred Qualifications Experience with analytics, machine learning, and deep learning on cloud platforms like Azure, focusing on time series forecasting, customer insights, and market analysis using Python, SQL, or PySpark. Knowledge of Data Engineering, Cloud Platforms, and MLOps to facilitate communication across multi-functional teams.
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