Crowe Horwath LLP is one of the largest public accounting and consulting firms in the United States. Under its core purpose of “Building Value with Values®,” Crowe uses its deep industry expertise to provide audit services to public and private entities, while also helping clients reach their goals with tax, advisory, risk and performance services. With offices coast to coast and 3,000 personnel, Crowe is recognized by many organizations as one of the country's best places to work. Crowe serves clients worldwide as an independent member of Crowe Horwath International, one of the largest global accounting networks in the world, consisting of more than 150 independent accounting and advisory services firms in more than 100 countries around the world.
Leverage large sets of structured and unstructured data to develop tactical and strategic insights. Collaborate with analytic and data teams to set objectives, approaches, and work plans. Research and evaluate new analytical methodologies, approaches, and solutions. Develop and validate statistical forecasting models and tools. Interpret and communicate analytic results to analytical and non-analytical business partners and executive decision makers.
Given substantial growth and impact at Crowe, the machine learning team has formed into an official unit, Advanced Data Science, which is responsible for all machine learning and artificial intelligence throughout the firm. Projects are being worked currently, or in the near future, within every business unit and industry vertical. Links below are examples of two projects for public release, in the healthcare finance and financial services industries respectively.
This team works on a wide variety of projects utilizing numerous areas of machine learning, including: supervised regression/classification, unsupervised learning, anomaly detection, NLP, reinforcement learning, deep learning, forecasting, etc.
Both the Data Scientist – Statistics and Data Scientist – Modeling posted positions sit within the Advanced Data Science group.