FEDEX - Lead Data Analyst (8-10 yrs)

Job Purpose:

Design and implement processes and solutions associated with a wide variety of data sets used for data/text mining, analysis to support informed business decisions. Gain insight into key business and deliverables by examining structured and unstructured data from multiple disparate sources. Effectively use current and emerging technologies to evaluate trends and develop actionable insights and recommendations to management, via the information available for analysis. Learn to use data, statistical and quantitative analysis, to drive decision making.

Accountabilities:

- Import, clean, transform, validate data from RDBMS (Oracle, Teradata) with the purpose of understanding or making conclusions from the data for decision making.

- Able to transform large volume data into information and information into insight.

- Answer business questions by using appropriate statistical techniques on available data to improve key success metrics related to yield management and revenue generation.

- Produce a variety of reports, graphs, summaries, and presentations that convey analytic results and align with business needs.

- Provides consultation and recommend and implement process improvements for timeliness, relevance, and presentation.

- Presenting senior executives with strong storytelling capability to drive insights out of data. Presents/frames business scenarios in ways that are meaningful and depicts their findings in easy-to-understand terms

Qualifications & Specifications:

- Bachelor's degree in information systems, computer science, or a quantitative discipline such as mathematics, engineering, operations research, economics & statistics. Masters degree in relevant specification will be first preference.

- Experience of at least 8-108 years of analytics, informatics and statistics.

- Experience in product marketing analytics, impact analysis is a plus

- Must have - SQL & Python experience , with exposure to any visualization tools (PowerBI, Tableau)

- Good to have - cloud computing, big data, Azure, NLP, ML.