Senior Data Scientist – Shopping Experience, Search

🕒 Abril 15

🗣️🇺🇸🇬🇧 Inglês obrigatório

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Logo of Instacart

Instacart

1001 - 5000 funcionários

Fundada em 2012

🛍️ Comércio Eletrônico

🚗 Transporte

🛒 Varejo

💰 $232.000.000 Venture Round em 2021-11

eCommerce • Transport • Retail

A Instacart é uma empresa que oferece uma abordagem flexível de trabalho enquanto transforma o setor de supermercados. Ela presta um serviço essencial ao entregar compras de supermercado e itens para a casa na porta dos clientes em até 30 minutos. A Instacart oferece oportunidades de ganho seguras e flexíveis para personal shoppers e enfrenta desafios como redirecionar entregas durante nevascas e conectar clientes a cupons e promoções. Seu objetivo é ser o sistema operacional do setor de supermercados, ajudando os clientes a economizar tempo para outras atividades. A Instacart valoriza diversidade, equidade e pertencimento em sua cultura de trabalho.

Descrição

• Own core Search metrics and funnels end to end (e.g., query → impression → engagement → cart adds), including defining guardrails, monitoring performance across platforms and segments, and diagnosing conversion gaps. • Design, run, and interpret experiments across ranking, retrieval, and search UX (e.g., relevance model changes, query understanding, result layouts), turning ambiguous or conflicting outcomes into crisp, data-driven recommendations. • Partner with Product, Engineering, and ML to prioritize opportunities, size impact, and influence the roadmap for relevance, quality, and latency improvements that unlock measurable business outcomes. • Build deep diagnostic analyses by query class, price point, surface, and customer lifecycle to pinpoint where and why Search underperforms and specify concrete changes that will move key outcomes. • Connect offline model evaluation with online and business metrics by collaborating with ML partners on evaluation design, ensuring model changes reliably improve end-user experience—not just offline scores. • Improve data quality, instrumentation, and metric definitions for Search so that teams can reason about performance with clarity, consistency, and speed.

🎯 Requisitos

• 5+ years of experience in data science or product analytics, with a track record of impact on consumer-facing products. • Advanced SQL proficiency, including complex joins and window functions, working with large-scale datasets in modern data warehouses (e.g., Snowflake, BigQuery, Redshift). • Proficiency in Python or R for analysis, experimentation, and modeling. • Hands-on experience designing and analyzing A/B tests end to end, including metric selection, power and sample sizing, covariate adjustment, and decision-making under uncertainty. • Demonstrated ability to define success metrics, decompose ambiguous product problems, and deliver clear, opinionated recommendations to Product and Engineering partners. • Excellent written and verbal communication skills; able to tailor complex analyses for both technical and non-technical audiences. • Bachelor’s degree in a quantitative field (e.g., Statistics, Computer Science, Mathematics, Economics, Engineering) or equivalent practical experience. • Comfort using modern AI tooling (e.g., Claude, code assistants, PromptQL) to accelerate analysis, experimentation, and communication while exercising strong judgment on quality and reliability.

🏖️ Benefícios

• health insurance • retirement plans • paid time off • flexible work arrangements • professional development • bonuses • stock options • equipment allowances • wellness programs

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