Decision Scientist (Test and learn, Reporting)

About the Role

Fractal Analytics is seeking an experienced Decision Scientist to lead test-and-learn initiatives across insurance products and member experiences. This role combines deep statistical rigor with consulting acumen: you will partner with product, marketing, and operations teams to frame business questions, design experiments, measure incremental impact, and translate results into clear, actionable recommendations. Beyond testing execution, you will leverage data modeling, analytics, and quantitative thinking to solve problems across the full value chain—from member acquisition and onboarding through engagement, retention, and lifetime value. This is an analytics consulting role ideal for candidates who combine strong experimental design and statistical skills with business acumen, intellectual curiosity, and the ability to translate complex technical findings into clear recommendations for cross-functional stakeholders.

Responsibilities

• Problem Scoping & Consulting Partnership
  • Work closely with stakeholders across product, marketing, operations, and strategy to understand business objectives and challenges.
  • Translate business questions into testable hypotheses; frame problems in statistical and analytical terms.
  • Scope test-and-learn initiatives within the broader value chain—understanding how acquisition, engagement, retention, and LTV connect to overall business objectives.
  • Identify data requirements and integration needs; partner with data engineering and analytics teams to prepare datasets.
• Test Design & Experimental Methodology
  • Design A/B tests, multivariate tests, and holdout/control experiments; define treatment, control, and sample allocation strategies.
  • Apply power analysis and sample size calculations to ensure statistical rigor; document assumptions and methodology.
  • Use Mastercard APT to configure, execute, and monitor test cells and measure incremental lift against control groups.
  • Design for real-world constraints: seasonality, holdout group limitations, technical feasibility, and compliance requirements.
• Data Analysis & Insights Extraction
  • Execute SQL and Python queries to extract, validate, and prepare test results and outcome data.
  • Apply statistical testing, confidence interval estimation, and causal inference methods to measure incremental lift and validate results.
  • Use Adobe Analytics to track experiment performance, segment results by customer cohort, and identify interaction effects.
  • Build LTV models to estimate long-term impact of treatments on customer value, retention curves, and profitability.
  • Conduct sensitivity analysis and validate findings against alternative model specifications.
• Recommendations & Actionability
  • Translate incremental lift, LTV impact, and statistical findings into clear, business-focused recommendations.
  • Quantify business impact: "Implementing this change will lift acquisition by X%, generating $Y in incremental revenue."
  • Design communication materials and visualizations for peer review, leadership, and operational execution teams.
  • Prioritize recommendations by impact, feasibility, and alignment with strategic objectives.
• End-to-End Analytics & Data Integration
  • Identify, gather, and integrate disparate data sources: digital (Adobe Analytics, clickstream), transactional, campaign, and third-party data.
  • Apply data quality techniques, validation checks, and documentation standards to ensure analytical rigor.
  • Build analytical datasets and dashboards to support ongoing monitoring and learning from test initiatives.
  • Document data lineage, assumptions, and methodology to support peer review and compliance requirements.
• Thought Partnership & Organizational Learning
  • Advocate for test-and-learn as a discipline; educate stakeholders on experimental design, statistical concepts, and best practices.
  • Build organizational capabilities: document playbooks and share learning across teams.
  • Collaborate with Fractal partners and subject matter experts to stay current on insurance, customer experience, and analytics best practices.

Requirements

• Education & Experience
  • Bachelor's degree in Economics, Finance, Statistics, Mathematics, Operations Research, Data Science, or related quantitative field.
  • 4+ years of experience in analytics, data science, or quantitative business roles (financial services, insurance, or consumer tech preferred); OR advanced quantitative degree with 3+ years of relevant experience.
• Test & Experimentation
  • 5+ years designing and analyzing A/B tests, multivariate tests, and holdout/control experiments.
  • 3+ years with Mastercard APT or comparable incrementality testing platforms.
  • Deep expertise in experimental design, power analysis, hypothesis testing, and statistical significance.
• Data & Analytics Foundations
  • Intermediate to advanced SQL: ability to query databases, build custom datasets, conduct exploratory analysis, and validate data quality.
  • Intermediate to advanced Python: data manipulation, statistical analysis, exploratory data analysis, and automation.
  • Strong data visualization skills: ability to communicate findings clearly using Tableau, Looker, Power BI, or similar tools.
  • Understanding of data quality, validation, and documentation; experience integrating data from multiple sources.
• Analytics & Statistical Methods
  • Proven competency in statistical techniques: regression analysis, causal inference, cohort analysis, and other quantitative methods.
  • Experience building analytical models and applying them to business problems.
  • Understanding of how to translate statistical findings into business recommendations.

Preferred Qualifications

• 3+ years of hands-on experience with Adobe Analytics, including funnel analysis, customer journey mapping, and experiment performance tracking.
• Experience building or applying LTV models to evaluate customer value, retention, and lifetime profitability.
• Track record running test-and-learn programs for insurance products (auto, home, umbrella, or related lines) or financial services products.
• Experience working in consulting or advisory roles; ability to partner with cross-functional teams and translate technical findings for non-technical audiences.
• Familiarity with Financial Services and Insurance, customer acquisition, onboarding, or member experience workflows.

Location

San Antonio/Dallas (Texas)

Pay

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the current range is $110,000 - $130,000. In addition, you may be eligible for a discretionary bonus for the current performance period.

Benefits

• Health, dental, vision, life insurance, and disability plans (eligible from the first day of employment).
• Company 401(k) Plan (eligible after 30 days of employment).
• 11 paid holidays.
• 12 weeks of Parental Leave.
• Flexible PTO policy ("free time" for sick time or vacation).