Tavis Barr

Tavis Barr is an economist, statistician, and data scientist with extensive experience in behavioral modeling and labor market research, business operations analytics, and software development. Expert in both classical statistics and machine learning techniques, including neural nets, NLP, and time series. Full stack software/data engineer. Currently Tavis is the Principal Data Scientist at Russell Reynolds, New York. Where he models business operations including automated white space target company recommendations, bespoke project pricing recommender and error detector, employee workload optimization, client feedback sentiment detection, client potential attrition detection, automated candidate long list generation. he is responsible for development and maintenance of complete MLOps platform. Also generate analysis for white papers.

Products used: Databricks, Spark (SparkNLP, BigDL), Python (Pandas, SkiKitLearn, Stats Models, LifeLines), Scala, Java, R, Cassandra, T-SQL, Neo4J, Kafka, Kubernetes, PowerBI. He has a Ph.D. In Economics from Columbia University (2002), a M.Phil. In Economics, Columbia University, (1999), a M.A. In Economics, Boston University, (1994), and a B.A. In Economics (Computer Science minor), Boston University (1994).