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Develop data science solutions for payments across Square and Cash App. Build AI-powered tools, ETL pipelines, dashboards, machine learning models, experiments, and cloud data systems. Partner with Product, Engineering, Finance, and Operations to improve payment success, cost efficiency, risk mitigation, and decision-making. Translate business needs into practical solutions, research questions independently, and operationalize data processes and infrastructure.

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Fetch

Data Scientist

8 Hours Ago

Remote

Canada

Senior level

AdTech • Big Data • Marketing Tech • Mobile • Grocery & Supermarkets • Consumer Packaged Goods (CPG)

Leads company-wide measurement and causal strategy, defining canonical metrics, semantic data architecture, experimentation standards, and strategic models such as marketing mix, elasticity, incentive sensitivity, and forecasting. Partners with engineering and analytics teams to build scalable, production-ready analytical frameworks, improve scientific rigor, and guide executive decisions. Provides organization-wide technical leadership, develops modeling standards, and applies advanced statistical and causal methods to high-impact business problems.

Top Skills: DbtExperimentation PlatformsPythonSnowflakeSQL

We are looking for a data-driven problem solver with strong statistical expertise to join our growing data science team. In this role, you’ll play a pivotal part in driving product innovation through rigorous experimentation, measurement, and insight generation. You'll collaborate with engineers, designers, and product managers to guide strategic decisions that impact millions of users.

Responsibilities

Design and evaluate controlled experiments (A/B tests) and quasi-experiments to inform product and business decisions.
Build and maintain automated pipelines for experiment tracking, analysis, and reporting.
Identify metrics, set success criteria, and quantify trade-offs in product features and changes.
Partner with cross-functional teams to embed a culture of data-informed decision-making.
Present findings to stakeholders with clarity, making statistical results actionable for the business.

Qualifications

Bachelor’s in Statistics, Data Science, Computer Science, or related field.
2+ years of experience in product analytics, experimentation, or applied statistics.
Solid knowledge of statistical inference, hypothesis testing, power analysis, and regression models.
Proficient in SQL and Python (or R), with experience analyzing large-scale data.
Strong data visualization skills; able to tell compelling stories with data.
Experience working closely with product or engineering teams in fast-paced environments.

Bonus Points

Experience with experimentation platforms or custom A/B testing frameworks.
Familiarity with online metrics, feature rollouts, or cohort-based analyses.
Exposure to techniques such as CUPED, variance reduction, or sequential testing.

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