Hands-on design and development of machine learning and AI models and validate models to the highest standards of accuracy, consistency, and business relevance
Identify and clear roadblocks to project deadlines and successful adoption; partner with Business and EDM IT teams to escalate and influence clearing the roadblocks promptly
Present project updates and demonstrate new capabilities to executive leadership audience
Lead Data Scientist team to by delegating and coordinating deliverables
Collaborate with IT EDM team to build and maximize value from Databricks platform and establishing new data pipelines
Partner with business, analytics, and finance teams to set and exceed value creation goals from Data Science models
Requirements
12+ years of overall analytics experience, can be inclusive of post graduate work
2+ years of managing teams or large projects in Data Science, Analytics, Business Intelligence, and Data Product management
Education: We require a degree in one of the following fields: Business Analytics, Economics, Operations Research, Engineering, Computer Science, Statistics, Mathematics, or Econometrics, or a similarly related analytical field.
Alternatively, a Master's degree can substitute for 1 year of experience, while a PhD can substitute for 3 years of experience.
10+ years of experience of Data Science model development with a combination of: Bayesian statistics, Regression analysis (beyond linear regression), Forecast/predictive analytics, Multivariate testing, Implement large-scale optimization models (mixed integer and linear programming, genetic algorithms), Use optimization packages such as Gurobi, CPlex, or others
10+ years of Data Engineering and Manipulation experience working in a cloud environment: Databricks, Microsoft Azure, Google BigQuery or AWS cloud platforms.
Familiarity with Azure and Databricks preferred.
Experience with practical machine learning using frameworks such as scikit-learn, H2O, TensorFlow, Caffe, or Mllib; AI Agent bricks experience ideal