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Replit
Replit
51 – 200 Darbinieki
H1B vīzas sponsorsB2BMākslīgais intelekts
Replit ir sadarbībā balstīta programmatūras izstrādes platforma, kas ļauj cilvēkiem veidot un kopīgot lietotnes no jebkuras vietas un ar jebkuru ierīci. Tās vairāku lietotāju vide atbalsta komandas darbu reāllaikā, savukārt ar mākslīgo intelektu darbinātais Generate Code palīdz lietotājiem pārvērst idejas funkcionējošā kodā un racionalizēt izstrādi. Uzņēmums darbojas mākslīgā intelekta un B2B programmatūras krustpunktā, un tā produkts ir paredzēts izstrādātājiem un komandām, kas kopīgi veido programmatūru.
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Vakances uzņēmumā

Senior Growth Data Scientist at Replit

Lead growth data science for Replit’s natural-language app creation platform, spanning experimentation, monetization, segmentation, and recommendations. Work with Product, Engineering, and Data Engineering teams.

USAmerikas Savienotās ValstisCAKalifornija
250 000 $ – 327 000 $ / gads
HibrīdiPilna slodzeVidējais līmenisVecākais speciālistsNepieciešamā Valoda: angļuDatu zinātnieks
PythonSQL

Apraksts

  • Lead data science across major growth initiatives, partnering with Product Managers and engineers from problem definition and sizing through launch and results review.
  • Design experiments and metrics for timely, reliable decisions when retention results take time, using CUPED, sequential testing, and validated short-term proxy metrics.
  • Set experimentation standards for Replit’s busiest product surfaces, defining metrics and guardrails and identifying broken tests.
  • Apply quasi-experimental methods, including difference-in-differences, synthetic controls, and regression discontinuity, when randomized tests are impractical.
  • Shape data science for personalization and recommendations, from problem definition and offline and online evaluation to measuring incremental lift.
  • Model the economics of a freemium, usage-based product, including credit use, conversion, pricing, and limits.
  • Build user and project segments from behavioral and content signals using methods such as embeddings and clustering.
  • Work with Data Engineering to build shared metrics and experimentation tools.

Prasības

  • At least six years in data science, including substantial work in growth or experimentation for high-scale prosumer, product-led growth, or self-serve products.
  • Data science experience at a fast-growing startup, building metrics, datasets, and experimentation practices with limited existing infrastructure.
  • Strong command of experimental design and statistical inference, including making reliable decisions with short readout windows and slow-moving outcomes.
  • Experience establishing experimentation standards or platforms used by multiple teams.
  • Expertise in SQL and Python.
  • Evidence that your analysis changed what a team shipped, and ability to influence senior Product and Engineering leaders.
  • Extensive practical use of AI tools to accelerate your work.
  • Ability to build your own datasets in dbt is preferred.
  • Experience analyzing pricing, packaging, or monetization for usage- or credit-based products is preferred.
  • International or mobile growth experience is preferred.
  • A master’s or doctoral degree in statistics, economics, computer science, or another quantitative field is preferred.
  • Experience with multi-armed bandits or adaptive experimentation is a bonus.
  • Familiarity with developer tools, AI products, or creator platforms is a bonus.
  • Able to work from the Foster City, California office three days per week.
  • Legally authorized to work in the United States.

Priekšrocības

  • Competitive salary and equity.
  • 401(k) plan with a 4% employer match in the United States.
  • Health, dental, vision, and life insurance.
  • Short- and long-term disability coverage.
  • Paid parental, medical, and caregiver leave.
  • Flexible time off and holidays.
  • Commuter benefits for in-office employees in the United States.
  • Monthly wellness stipend.
  • Autonomous work environment.
  • Reimbursement for in-office setup.
  • Quarterly team gatherings.
  • On-site amenities.

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