Lead Data Scientist (Experimentation)

Location: Hybrid role based within a 180-mile radius of Bloomington, Illinois; Dunwoody, Georgia; Richardson, Texas; or Tempe, Arizona, with regular office attendance. Applicants must be eligible to work lawfully in the U.S. immediately; visa sponsorship is not available.

Salary: $110,000–$160,000 per year, with potential yearly incentive pay of up to 15% of base salary.

Company

hirify.global is an insurance company focused on helping customers, investing in communities, and improving people's lives.

What you will do

• Formulate hypotheses and design experiments, including A/B tests, to measure the impact of strategic decisions.
• Develop and validate advanced analytic models, datasets, and data-driven solutions.
• Collaborate with business partners and technical teams to scope solutions and define project decision points.
• Present statistical concepts, technical topics, and actionable results to technical and non-technical stakeholders.
• Recommend data collection, integration, and retention strategies based on business requirements and best practices.
• Lead and mentor data scientists, interns, and technical work teams while reviewing other model development work.

Requirements

• Completed master's degree or another advanced degree in statistics, quantitative marketing, experimental psychology, operations research, management science, industrial engineering, or a related analytical field, plus 3+ years of predictive model-building experience.
• Practical experience with A/B testing and experimental design in business contexts.
• Ability to explain statistical significance, confidence intervals, regression models, and related concepts to business partners.
• Experience with generalized linear models and at least one of time series analysis, cluster analysis, tree-based algorithms, or neural networks.
• Experience with at least one statistical programming language: Python, R, or SAS.
• Strong communication and stakeholder-management skills, including experience designing scalable data science solutions in a regulated environment.

Nice to have

• Experience with mixed linear and non-linear modeling methodologies.
• Experience with causal inference or difference-in-differences estimation.
• Experience with cloud environments such as AWS or Linux.
• Experience in insurance, healthcare, or finance.

Culture & Benefits

• Hybrid work environment with a standard 38:45-hour work week.
• Annual raises, incentive compensation, health and wellbeing programs, and multiple healthcare plan options.
• Training programs, tuition assistance, mentoring, and employee resource groups.
• Paid time off, up to 20 days initially, parental leave, paid holidays, and community service or education support days.
• Retirement benefits through a 401(k) plan with company contributions of up to 7% of salary.

Hiring process

• Initial application review followed by a video-recording assessment.
• Live video interviews covering role-play with a data science business partner, code and graphical output interpretation, and technical expertise.
• Final candidates may complete an in-person final loop interview.