What your main responsibilities are
- Design and implement processes and solutions associated with a wide variety of datasets used for data/text mining and analysis to support informed business decisions.
- Gain insight into key business drivers 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 for management by leveraging available data.
- Learn to use data, statistical techniques, and quantitative analysis to drive decision-making.
What you'll be working on
- Import, clean, transform, and validate data from RDBMS sources (Oracle, Teradata) with the purpose of understanding or drawing conclusions to support decision-making.
- Transform large volumes of data into information and information into insights.
- Answer business questions using appropriate statistical techniques on available data to improve key success metrics related to yield management and revenue generation.
- Produce various reports, graphs, summaries, and presentations that convey analytical results and align with business needs.
- Provide consultation, recommend improvements, and implement process enhancements for timeliness, relevance, and presentation quality.
- Present insights to senior executives using strong storytelling capabilities. Frame business scenarios in meaningful ways and depict findings in easy-to-understand terms.
What we are looking for
- Bachelor's degree in information systems, computer science, or a quantitative discipline such as mathematics, engineering, operations research, or economics & statistics. A Master's degree in a relevant specialization is preferred.
- 57 years of experience in analytics, informatics, or statistics.
- Experience in product marketing analytics or impact analysis is a plus.
- Must have: SQL and Python experience, with exposure to visualization tools such as Power BI or Tableau.
- Good to have: Cloud computing, big data technologies, Azure, NLP, ML.
