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Data Scientist

Vaga remota de 20408 S&M - Sales - Square RevOps & Enablement com fit claro de localização do candidato.

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Países elegíveis1 país aceito

Sinal de senioridadeNível aberto

Modelo de trabalhoRemoto

Locais aceitos para candidatos

Estados Unidos

Resumo da vaga

Conteúdo da vaga extraído em seções para revisão mais rápida.

Own performance measurement for your subdomain: monitoring the metrics that matter (wins, new revenue, funnel conversion, rep productivity), reporting against plan, and presenting the story in business reviews with sales leadership
Lead investigations into performance questions ("why is X down?", "how can we improve Y?"), decomposing KPIs from first principles and designing experiments to test what actually works
Take on large, ambiguous projects autonomously: scoping the problem, finding the right data, thinking critically about what it can and can't tell you, and landing the results with stakeholders
Own and evolve your subdomain's data foundation, and partner with Sales DS peers on shared metrics, attribution logic, and cross-cutting analyses
Translate data into business context: telling the story behind the numbers, pushing back on hypotheses with evidence, and building trust with senior sales, finance, and operations leaders
Work AI-natively: use agents throughout your workflow and pioneer new ways of applying AI to the hardest problems in the sales domain
Build self-serve dashboards and datasets that let the sales org answer its own questions
Raise the bar for the team's analytical rigor, communication, and AI-enabled ways of working

Minimum of 8 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree; or a PhD with 3 years experience; or equivalent experience
Advanced SQL and strong Python; comfort owning the full stack from ETL to analysis to visualization
Strong statistical foundations: experiment design, causal inference, funnel and cohort analysis, and forecasting; you can interpret results with rigor and explain the concepts behind them
A track record of running large projects end to end with minimal direction; you're the person leadership trusts when the numbers matter
Strong critical thinking: you know when to move fast and when to slow down on a problem with big consequences, and you pressure-test your own conclusions
Exceptional communication: you can present performance to executives, translate technical nuance for non-technical partners, and write analysis documents that stand on its own
Enthusiasm for building with AI, and curiosity about how far it can be pushed in data science work
Curiosity about unfamiliar data and how sales organizations actually work, and the empathy to partner well with the people on the frontline

SQL, Snowflake, Databricks, Python (Pandas, NumPy)
Looker, Omni, Airflow, dbt-style ETL patterns
Agentic AI: agent skills and bots, automated reporting workflows, in-house tooling
Salesforce and the modern GTM data stack
A/B, matched-market, and causal testing

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