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.

Crowe Horwath is looking to expand its Machine Learning team with additional practitioners to invest in additional products and services in this disruptive area.  Applicants should have advanced degrees and experience with Machine Learning, a.k.a. Artificial Intelligence or Cognitive Learning.

• 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.

The machine learning team is very new for Crowe, and has already had substantial growth and impact. The team now sits within the Applied Technology business unit, and has focused on Healthcare related projects for creating machine learning models to fix and automate revenue cycle exceptions:http://www.crowehorwath.com/industries/healthcare/revenue-cycle/exceptions-resolution.aspx. Future growth of the team will allow projects to be worked throughout the firm, covering all industries Crowe operates in.

Education

• Advanced degree (Masters at a minimum) or other advanced certification in a quantitative field in one or more of the following:
  • Statistics
  • Engineering
  • Computer Science
  • Data Science
  • Mathematics
  • Physics
  • [or similar academic pedigree]

Experience

• 4+ years experience in advanced analytics and machine learning model development and validation.
• 2+ years experience working in industry, leading analytic-based projects, and delivering results within scope, funding, and duration.

Modeling Experience

• Neural Networks (Feed-forward, CNN, RNN, etc.)
• Parallel Processing (CPU & GPU)
• Cluster and cloud computing: Spark, Mesos, Azure ML, etc.

Special Skills

• Excellent communication skills
• Expert level programming skills in R
• Experience with a statistical package and various programming languages such as R, Python, Java, C++, SAS, Matlab, etc.
• Experience writing SQL queries and linking to enable read/write to the database.
• The capacity for a high degree of autonomy and out-of-the-box thinking