Howrecruit
Senior Data Analyst / Experimental Designer Expert
$170k–$210k USD + equity + annual bonus + incredible benefits
Remote (US / Canada)
Profitable Startup
Howrecruit has been retained by a profitable, high-growth home services platform to hire a Senior Data Analyst who lives and breathes experimental design. This isn't a role where experimentation is just one item on a long list. It's the core of what you'll do. You'll own the end-to-end experimentation program, designing rigorous A / B tests that directly shape product strategy and business decisions.
If you're someone who gets excited about power calculations, debates the merits of sequential testing, and has strong opinions about when to use stratification vs. blocking, we want to talk to you.
What you'll do
Own the experimentation roadmap
Design, implement, and analyze sophisticated A / B tests and multivariate experiments that answer critical business questions
Be the experimentation subject matter expert
Educate stakeholders on experimental best practices, help them formulate testable hypotheses, and determine appropriate sample sizes and test durations
Navigate complexity: Handle challenges like network effects, interference between test groups, non-normal distributions, and multiple testing corrections
Drive statistical rigor: Choose appropriate statistical methods (frequentist, Bayesian, sequential testing) based on context, and clearly communicate tradeoffs
Partner with engineering: Collaborate on instrumentation and randomization strategies to ensure experiments are implemented correctly
Establish guardrail metrics: Define and monitor metrics that protect the user experience and business health during experimentation
Build experimentation infrastructure: Create frameworks, templates, and documentation that scale experimentation across the organization
Democratize insights: Translate complex experimental results into clear recommendations that drive action
Support ad-hoc analysis: Write SQL queries, build dashboards in Snowflake and future BI tools, and respond to data requests as needed
Requirements
Master's or PhD in Statistics, Mathematics, Economics, Biostatistics, Operations Research, or a related quantitative field (or equivalent advanced training in experimental design and statistical inference)
5+ years of hands-on experience designing and analyzing experiments in a tech, product, or high-growth environment (graduate research involving experimental design counts toward this)
Expert-level understanding of experimental design principles randomization, power analysis, multiple testing corrections, variance reduction techniques, and experimental validity (internal, external, construct)
Deep statistical knowledge confidence intervals, hypothesis testing, regression analysis, ANOVA, and when to apply parametric vs. non-parametric methods
Advanced SQL skills ability to write complex queries to calculate test metrics, detect data quality issues, and perform pre / post analysis
Strong Python skills proficiency with statistical libraries (scipy, statsmodels, or similar) for experiment analysis and simulation
Experience with Snowflake or similar cloud data warehouses
Track record of impact examples where your experimental insights led to meaningful product or business changes
Exceptional communication skills ability to explain statistical concepts like p-values, confidence intervals, and sample size calculations to non-technical stakeholders
Bonus points for
PhD with dissertation focused on experimental design, causal inference, or applied statistics
Familiarity with advanced methods like difference-in-differences, synthetic controls, or instrumental variables
Publications, conference talks, or blog posts about experimentation
Experience building internal experimentation tools or frameworks
Formal training in design of experiments (DOE) or clinical trial methodology
A Successful Candidate
Is an experimentation evangelist; You're passionate about rigorous testing and help others understand why shortcuts lead to bad decisions
Balances theory with practice; You bring academic rigor but know how to apply it in fast-moving business contexts
Is naturally curious; You don't just run tests you dig into surprising results and form hypotheses about user behaviour
Is a clear communicator; You can explain why an experiment is underpowered or biased in a way that resonates with PMs and executives
Is proactive and independent; You identify opportunities for testing, advocate for experiments, and drive them to completion
Is collaborative; You work cross-functionally with product, engineering, marketing, and operations to build an experimentation culture
If you're an experimentation expert with strong quantitative training who wants to build a world-class testing program at a profitable, fast-growing startup, we'd love to hear from you. This is a chance to have outsized impact and work behind the scenes of one of the most successful bootstrapped companies you've never heard of.
#J-18808-Ljbffr
$170k–$210k USD + equity + annual bonus + incredible benefits
Remote (US / Canada)
Profitable Startup
Howrecruit has been retained by a profitable, high-growth home services platform to hire a Senior Data Analyst who lives and breathes experimental design. This isn't a role where experimentation is just one item on a long list. It's the core of what you'll do. You'll own the end-to-end experimentation program, designing rigorous A / B tests that directly shape product strategy and business decisions.
If you're someone who gets excited about power calculations, debates the merits of sequential testing, and has strong opinions about when to use stratification vs. blocking, we want to talk to you.
What you'll do
Own the experimentation roadmap
Design, implement, and analyze sophisticated A / B tests and multivariate experiments that answer critical business questions
Be the experimentation subject matter expert
Educate stakeholders on experimental best practices, help them formulate testable hypotheses, and determine appropriate sample sizes and test durations
Navigate complexity: Handle challenges like network effects, interference between test groups, non-normal distributions, and multiple testing corrections
Drive statistical rigor: Choose appropriate statistical methods (frequentist, Bayesian, sequential testing) based on context, and clearly communicate tradeoffs
Partner with engineering: Collaborate on instrumentation and randomization strategies to ensure experiments are implemented correctly
Establish guardrail metrics: Define and monitor metrics that protect the user experience and business health during experimentation
Build experimentation infrastructure: Create frameworks, templates, and documentation that scale experimentation across the organization
Democratize insights: Translate complex experimental results into clear recommendations that drive action
Support ad-hoc analysis: Write SQL queries, build dashboards in Snowflake and future BI tools, and respond to data requests as needed
Requirements
Master's or PhD in Statistics, Mathematics, Economics, Biostatistics, Operations Research, or a related quantitative field (or equivalent advanced training in experimental design and statistical inference)
5+ years of hands-on experience designing and analyzing experiments in a tech, product, or high-growth environment (graduate research involving experimental design counts toward this)
Expert-level understanding of experimental design principles randomization, power analysis, multiple testing corrections, variance reduction techniques, and experimental validity (internal, external, construct)
Deep statistical knowledge confidence intervals, hypothesis testing, regression analysis, ANOVA, and when to apply parametric vs. non-parametric methods
Advanced SQL skills ability to write complex queries to calculate test metrics, detect data quality issues, and perform pre / post analysis
Strong Python skills proficiency with statistical libraries (scipy, statsmodels, or similar) for experiment analysis and simulation
Experience with Snowflake or similar cloud data warehouses
Track record of impact examples where your experimental insights led to meaningful product or business changes
Exceptional communication skills ability to explain statistical concepts like p-values, confidence intervals, and sample size calculations to non-technical stakeholders
Bonus points for
PhD with dissertation focused on experimental design, causal inference, or applied statistics
Familiarity with advanced methods like difference-in-differences, synthetic controls, or instrumental variables
Publications, conference talks, or blog posts about experimentation
Experience building internal experimentation tools or frameworks
Formal training in design of experiments (DOE) or clinical trial methodology
A Successful Candidate
Is an experimentation evangelist; You're passionate about rigorous testing and help others understand why shortcuts lead to bad decisions
Balances theory with practice; You bring academic rigor but know how to apply it in fast-moving business contexts
Is naturally curious; You don't just run tests you dig into surprising results and form hypotheses about user behaviour
Is a clear communicator; You can explain why an experiment is underpowered or biased in a way that resonates with PMs and executives
Is proactive and independent; You identify opportunities for testing, advocate for experiments, and drive them to completion
Is collaborative; You work cross-functionally with product, engineering, marketing, and operations to build an experimentation culture
If you're an experimentation expert with strong quantitative training who wants to build a world-class testing program at a profitable, fast-growing startup, we'd love to hear from you. This is a chance to have outsized impact and work behind the scenes of one of the most successful bootstrapped companies you've never heard of.
#J-18808-Ljbffr