Data Scientist

Develop software programs, algorithms and automated processes that cleanse, integrate and evaluate large data sets from multiple disparate sources

Manipulate large amounts of data across a diverse set of subject areas, collaborating with other data scientists and data engineers to prepare data pipelines for various modeling protocols

Build, validate, and maintain AI (Machine Learning (ML) /Deep learning) models, diagnose and optimize performance and develop statistical models and analysis for ad hoc business focused analysis

Communicate meaningful, actionable insights from large data and metadata sources to stakeholders

Able to communicate difficult concepts in a simple manner

Participate in projects and assignments of diverse scope

Advanced proficiency in R, Python, Spark, Hive (or other MR), and common scripting languages for E2E pipeline Advanced proficiency using SQL for efficient manipulation of large datasets in on prem and cloud distributed computing environments, such as Azure environments

Experience with ML and classical predictive techniques such as logistic regression, decision trees, nonlinear regressions, ANN/CNN, boosted trees, SVM, Tensorflow, visualization packages, and a track record for creating business impact with these methods

Ability to work both at a detailed level as well as to summarize findings and extrapolate knowledge to make strong recommendations for change

Ability to collaborate with cross functional teams and influence product and analytics roadmap, with a demonstrated proficiency in relationship building

Present problem analysis and recommended solutions in a creative and logical manner