Required Skills
Data Exploratory Analysis
Lead the development of new Predictive models working with internal stakeholders from gathering requirements to delivery
Perform data mining by applying machine learning and supervised learning algorithms.
Support advanced analytical and data mining efforts which could include but not limited to clustering, segmentation, logistic and multivariate regression, decision/CART trees, neural networks, time-series analysis, sentiment analysis, topic modeling, and Bayesian analysis
Visualize, interpret, report, and communicate data findings creatively in a various formats and audiences using Tableau, ggplot.
Integrate with cloud based web technologies via web services API.
Think creatively and work well both as part of a team and as an individual contributor.
QUALIFICATIONS
Degree in Machine Learning, Statistics, Applied Mathematics, Computer Science, Information Systems, or related quantitative disciplines, with a minimum of five years of relevant experience (Bachelor’s required, Master’s or PhD’s preferred)
Expert in analytical tools like R, SAS, SQL.
Have hands-on experience developing predictive models using analytical methods such as regression, decision trees, support vector machines, Random Forests, Neural Networks.
Have hands-on experience using relational database management systems (Oracle, Teradata, SQL Server, DB2 etc.)
Hands on experience in Java, Hadoop, HIVE, Scala, Apache Spark and MLLib – to include developing Machine Learning Algorithms in Spark MLLib and building real time models preferably in Spark MLLib.
Expertise in visualization tools like Tableau, ggplot is a plus.
Expertise in Python, Linux is a plus.
Exceptional ability to communicate and present findings clearly to both technical and non-technical audiences
Excellent interpersonal and collaboration skills
Experience working in health care domain is preferred.