Data Analyst

• Design, implement, and analyze A/B tests and other experimental designs (e.g., multivariate tests, holdout groups, switchback experiments) across product and marketing initiatives.
• Apply causal inference techniques - including difference-in-differences, propensity score matching, synthetic control, regression discontinuity, and instrumental variables - for scenarios where randomized experiments aren''t feasible.
• Determine appropriate statistical tests (t-tests, chi-square, ANOVA, non-parametric alternatives, sequential testing, Bayesian methods) based on data characteristics and business context.
• Calculate sample size and power requirements, and advise stakeholders on minimum detectable effect, test duration, and experiment feasibility before launch.
• Build reusable Python-based analysis pipelines and tooling (e.g., using pandas, numpy, scipy, statsmodels) to standardize experiment analysis and reduce time-to-insight.
• Write and optimize SQL to extract, transform, and validate experiment and behavioral data from large, complex datasets.
• Partner with Product Managers, Engineers, and Marketers to scope experiments, define success metrics and guardrail metrics, and ensure proper randomization and instrumentation.
• Proactively identify data quality issues, sample ratio mismatches, novelty effects, and other threats to experiment validity, and flag them before they affect decisions.
• Communicate experiment design, methodology, and results clearly to stakeholders with varying levels of technical expertise, through written reports and presentations.
• Build dashboards and visualizations (e.g., in Tableau, Looker, or Python plotting libraries) to track experiment health and results in near real time.
• Contribute to the evolution of the company''s experimentation platform, standards, and playbooks.

The ideal candidate combines strong statistical fundamentals with hands-on experience with statistics, machine learning and AI; and is comfortable owning experiments end-to-end (design, instrumentation review, analysis, readout), and can clearly communicate methodology and results to both technical and non-technical audiences., * Bachelor''s or Master''s degree in Statistics, Data Science, Economics, Mathematics, Computer Science, or a related quantitative field.

• 5+ years of hands-on experience in data analysis, with 3+ years specifically designing and analyzing A/B tests or experiments in an industry setting.
• Strong proficiency in Python for statistical analysis and data manipulation (pandas, numpy, scipy, statsmodels, or similar).
• Demonstrated expertise in statistical hypothesis testing (t-tests, chi-square, ANOVA) and in causal inference methods beyond simple A/B testing (e.g., diff-in-diff, matching methods, regression discontinuity, uplift modeling)
• Practical understanding of experimental design concepts: randomization, power analysis, minimum detectable effect, novelty/primacy effects, network effects, and common pitfalls (e.g., peeking, multiple comparisons, Simpson''s paradox).
• Ability to translate ambiguous business questions into rigorous, testable analyses and communicate the resulting trade-offs clearly.
• Experience presenting technical findings to non-technical stakeholders, including executives, in a clear and compelling way.
• Comfort working with large, sometimes messy, real-world data and identifying/troubleshooting data integrity issues., * Experience with experimentation platforms (e.g., Adobe [preferred], Optimizely, Statsig, GrowthBook, or in-house tooling) and/or building internal experimentation frameworks.
• Familiarity with Bayesian statistics and sequential/always-valid testing methods.
• Experience with version control (Git) and writing production-quality, reusable analysis code.
• Background in a consumer product, subscription, streaming, or e-commerce environment.
• Familiarity with data visualization tools such as Tableau or Looker.
• Exposure to experimental design in marketing (e.g., geo-testing, media mix modeling) in addition to product experimentation.

Our benefits package includes:

• Comprehensive medical benefits
• Competitive pay
• 401(k) retirement plan
• …and much more!

About, INSPYR Solutions

Technology, is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients'' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about us at inspyrsolutions.com. INSPYR Solutions provides Equal Employment Opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, INSPYR Solutions complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities.