F&G is looking to hire for a Data Scientist - Retail

The Data Scientist position will provide leadership for data science initiatives and derive actionable insights from complex datasets. This position will play a key role in shaping advanced analytics, developing advanced analytical models, and mentoring team members. This position will have responsibility to collaborate closely with teams to identify opportunities, solve challenging problems, and drive innovation across the organization.

Organization                                    

This position reports to the Director, Analytics and interacts with other members of Retail and the larger organization. This quantitative role will collaborate with IT, data engineers, advanced analytics developers, business stakeholders, and business leaders to evaluate and address business problems using advanced analytics and data science methods.

Duties and Responsibilities

• 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; interprets and communicates 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 un-clean, 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 contributes to 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.

Experience and Education Requirements

• Master's or PhD degree in a 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 tool (e.g., Tableau, Power BI, Jupyter Hub).

Preferred Requirements   

• 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

Knowledge, Skills, and Abilities

• Fluent in Python or R
• Fluent in statistical/mathematical software (e.g., scikit 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

Other Requirements

• Must be able to sit in front of a computer for extended periods of time
• Perform other functions, duties and projects as assigned
• Regular and punctual attendance
• Minimal travel required (less than 10%)

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