Candidate should have experience in some form of SQL (e.g. HIVE, PostgreSQL, MSSQL, etc.) and either Python or R for statistical application development. Experience in a Hadoop environment and / or statistical development tool (e.g. RapidMiner, Knime) a plus.
Data Scientist:
• Develop and communicate a deep understanding of client needs, perform analytical deep-dives to identify problems, opportunities and specific actions required
• Develop reproducible and deployable statistical applications on platform such as R/Python/Spark using techniques such as Regression, SVM, and Neural Networks
• Implementing processes that improve and lead to greater data quality
• Conducting statistical analyses to develop strategies
• Documenting all processes and research
• Building new algorithms and model training
• Executing projects involving analytics
• Identifying data patterns and trends
• Analyzing data to develop predictive models
• Creating, managing, and maintaining analytically rigorous data
• Possessing a solid machine learning foundation
• Proven record of successful statistical product delivery
• Ability to execute health insurance use cases via statistical applications such as R or Python
• Efficiently access data via multiple vectors (e.g. NFS, FTP, SSH, SQL, Sqoop, Flume, Spark)
• Significant experience with SQL and working with large datasets required
• Work with cross-functional teams (including Product Management, Engineering, and senior executives) to rapidly execute and iterate
• Noting anomaly detection and running diagnostics
• Performing graphical model analysis
• Strong verbal and written communication skills