Extract knowledge and insights from high volume, high dimensional data in order to investigate complex business problems through a range of data preparation, modeling, analysis and/or visualization techniques; this includes the use of advanced statistical analysis, algorithms, predictive modeling, experimentation and pattern recognition to create sustainable solutions that enable enhanced business performance.
Confer with business partners to identify questions and issues for data analysis and experiments.
Identify meaningful insights from large data and metadata sources; interpret and communicate insights and findings from analysis and experiments to product, service, and business managers.
Harden models for production deployment and monitor model performance over time.
Design and highlight scalable data infrastructure and pipelines for efficient data processing, storage, and analysis.
Stay abreast of emerging technologies and industry trends in data science, machine learning, and artificial intelligence, and evaluate their potential impact on our business.
Provide expertise on the risks and benefits of AI software created by external vendors
Follow and teach data science best practices, including CRISP-DM
Mentor and provide technical guidance to other team members, fostering a culture of collaboration and continuous learning.
Recommend technical stacks and capabilities to support advanced analytics from a data science perspective
Communicate findings and recommendations to non-technical audiences through compelling visualizations, reports, and presentations.
Collaborate with teammates, IT teams, and other partners to build technical solutions that solve problems, are reusable, scalable, fast, and maintainable with large datasets, both clean and unclean, to support advanced analytics
Initiate collaboration with customers, internal teams, and departments to build collaborative, cross-functional relationships to achieve mutual goals.
Question common practice and contribute to the improvement of processes and outputs
Teach, mentor, and provide work direction to interns and/or entry-level modelers.
Create and maintain process documentation and instructions for analyses conducted. Produces files and result summaries that are professional and communicate information effectively.
Requirements & Skills:
Master’s or PhD degree in mathematics, statistics, machine learning, data science, economics, computer science, operations research, or other quantitative field
8+ years of experience designing, building, and supporting advanced analytics models in a professional environment
Experience with database Rational Database Management System (RDBMS) technologies (e.g., SQL Server, Greenplum, Oracle).
Experience with big data technologies (e.g., Snowflake, Hadoop, Spark, Hive, Databricks, Azure).
Experience with data querying languages (e.g. Python, SQL)
Experience with data visualization tools (e.g., Tableau, Power BI, Jupyter Hub).
Experience with Life Insurance and Indexed Annuity data
Experience with cloud technologies such as Azure as it pertains to data and analytics
General understanding of non-analytics functions within an insurance company
Fluent in Python or R
Fluent in statistical/mathematical software (e.g., sci-kit learn in Jupyter Hub, modeling in R Studio, STATA, SAS, Statistica)
Ability to adhere to standard practices and use of version control tools such as GitHub/GitLab.
Thorough understanding of linear and logistic regression, SVMs, hybrid models, random forest, and other decision trees
Ability to make Feature selections and/or extractions
Familiar with machine learning practices to automate model selection and feature selection
Strong analytical, critical thinking, and problem-solving skills
Fast, adaptive learner
Ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
Exhibits flexibility and tolerance for ambiguity with the ability to thrive in a rapidly changing business environment
Results-oriented
Dedicated work ethic
Strong interpersonal communication skills, written and verbal
Excellent teamwork and relationship-building skills
