Snowflake6 days ago
Старший Data Scientist, GTM
Salary not specified
MARKET
15,900 ₽median for this role
Data Scientist · 115 jobs with disclosed pay
5,000half of the offers: 12,796–20,50043,793
The employer didn't disclose pay — compare with the market yourself.
Полная занятостьUS-CA-Menlo Park
Responsibilities
- 01Set the technical direction for a portfolio of AI & Machine Learning GTM decision systems spanning Sales and Marketing.
- 02Develop pipeline forecasting methods that model stage progression, conversion, deal timing
- 03Build account, lead, opportunity, and customer models that identify propensity, risk, potential, and likely next outcomes.
- 04Develop recommendation and next-best-action systems that determine where GTM teams should focus, which action to take, and when to take it.
- 05Apply causal inference, experimentation, and uplift modeling to measure the incremental impact of campaigns, sales activities, and customer interventions.
- 06Define common standards for point-in-time training, backtesting, calibration, ranking quality, treatment-effect evaluation, uncertainty, and realized business impact.
- 07Partner with GTM leaders and RevOps to identify high-value decisions, define interventions, and embed outputs into recurring workflows.
- 08Separate genuine customer and market movement from CRM changes, selection effects, territory shifts, instrumentation gaps, and model artifacts.
- 09Mentor scientists and raise technical standards across GTM Data Science and its partner teams.
Requirements
- 01Advanced degree in Statistics, Mathematics, Operations Research, Economics, Engineering, Computer Science, or a related quantitative field, or equivalent practical experience.
- 025+ years of experience building production-grade statistical or machine learning systems with meaningful business impact.
- 03A record of setting technical direction across ambiguous, cross-functional, or multi-team problem spaces.
- 04Deep expertise in several relevant areas, such as causal inference, experimentation, forecasting, propensity modeling, uplift modeling, ranking, or recommendation systems.
- 05Strong judgment about when to use predictive ML, causal methods, generative AI, or a simpler analytical approach.
- 06Experience translating business decisions into measurable objectives, interventions, evaluation designs, and production systems.
- 07Strong Python and SQL skills and experience working with large-scale data platforms.
- 08Experience operating models with monitoring, validation, versioning, reproducibility, and safe lifecycle management.
- 09Ability to work with imperfect CRM, marketing, product, and customer data while making assumptions and limitations explicit.
- 10Demonstrated ownership of high-stakes outputs used by business or executive stakeholders.
- 11Excellent communication, technical leadership, and cross-functional influence skills.