Data Analyst

Summary

Edkey is a company seeking a Data Scientist to join their multidisciplinary actuarial and data science team. The role focuses on designing and delivering analytical insights to improve core actuarial processes, utilizing statistical modeling, machine learning, and data engineering.

Responsibilities

• Create statistical models, algorithms, and machine learning solutions to enhance traditional actuarial processes and loss modeling assumptions
• Apply Python and/or R to develop, maintain, and support production and research models across lines of business
• Design and implement end-to-end model lifecycle components: requirements, development, validation, deployment, monitoring, and documentation
• Extract and profile data using SQL and work with data engineering partners to ensure model-ready datasets
• Collaborate with actuaries, product partners, data engineers, and stakeholders to align technical solutions with business strategy
• Translate model results and limitations into clear presentations and actionable recommendations for non-technical audiences
• Contribute to long-term tools and frameworks that scale modeling and analytic capabilities
• Stay current with research and state-of-the-industry techniques, proposing innovations where they add business value

Skills

• 2+ years of relevant industry or applied data science experience recommended
• Bachelor's degree required; preference for Master's in Statistics, Applied Mathematics, Data Science, Computer Science, Actuarial Science, or a related analytical field
• Hands-on experience in statistical modeling, inference, and building machine learning algorithms using Python and/or R
• Proficient in SQL and comfortable navigating relational databases to extract and transform attributes for modeling
• Demonstrated experience across the end-to-end modeling lifecycle (requirements, development, validation, monitoring)
• Strong written and verbal communication skills; able to present technical results to non-technical stakeholders
• Self-motivated, results-oriented, and effective as a collaborative team member with strong ownership of deliverables
• Candidates must be authorized to work in the U.S. without company sponsorship. confidential client will not support the STEM OPT I-983 Training Plan endorsement for this position
• Progress toward relevant actuarial or professional credentials (e.g., FCAS, FSA, CSPA)
• Familiarity with model deployment and reproducibility tools; experience with Unix, Git, Shiny, and R Markdown is a plus

Qualifications

Must Haves

• 2+ years of relevant industry or applied data science experience recommended
• Bachelor's degree required; preference for Master's in Statistics, Applied Mathematics, Data Science, Computer Science, Actuarial Science, or a related analytical field
• Hands-on experience in statistical modeling, inference, and building machine learning algorithms using Python and/or R
• Proficient in SQL and comfortable navigating relational databases to extract and transform attributes for modeling
• Demonstrated experience across the end-to-end modeling lifecycle (requirements, development, validation, monitoring)
• Strong written and verbal communication skills; able to present technical results to non-technical stakeholders
• Self-motivated, results-oriented, and effective as a collaborative team member with strong ownership of deliverables
• Candidates must be authorized to work in the U.S. without company sponsorship. confidential client will not support the STEM OPT I-983 Training Plan endorsement for this position

Nice to Haves

• progress toward relevant actuarial or professional credentials (e.g., FCAS, FSA, CSPA)
• Familiarity with model deployment and reproducibility tools; experience with Unix, Git, Shiny, and R Markdown is a plus

Benefits

• Total compensation may include additional elements such as bonuses, long-term incentives, and recognition programs.
• Confidential client offers a Hybrid or Remote arrangement depending on experience and role fit.
• Candidates living near an office (Columbus, OH; Chicago, IL; Hartford, CT; or Charlotte, NC) are expected to be in-office approximately 3 days per week (Tuesday–Thursday).
• Candidates not near an office may be eligible for a remote arrangement, with an expectation to come into an office as business needs require.