Senior Data Scientist, Sales Operations

CoreWeave•New York City, NY

10d•$135,000 - $198,000•Hybrid

About The Position

As a Senior Data Scientist, Sales Operations, you will play a pivotal role in shaping our commercial strategy and enabling data-driven decision making across the GTM organization. You will architect the data foundations for Sales, build advanced analytical and machine-learning models, and translate complex datasets into clear, strategic insights. Your work will directly guide forecasting, planning, segmentation, quota design, and GTM investments. You’ll collaborate closely with cross-functional leaders and influence decisions at the highest levels.

Requirements

6–10+ years of experience in data science, sales operations analytics, business intelligence, or commercial strategy roles within SaaS, cloud, infrastructure, or high-growth technology environments.
Expertise with SQL, Python/R, large-scale datasets, statistical modeling, machine-learning methods, and data visualization tools.
Demonstrated ability to translate analytical outputs into strategic GTM recommendations and influence Sales/RevOps leadership.
Experience building forecasting models, segmentation frameworks, propensity models, or other advanced analytics used to drive revenue outcomes.
Strong understanding of GTM motions, sales funnel mechanics, segmentation and targeting, territory/quota design, pipeline generation, and churn/expansion dynamics.
Proven ability to communicate data and analysis clearly to senior leadership, using structured narratives and decision-ready insights.
Bachelor’s degree in data science, statistics, mathematics, economics, engineering, business, or related field; advanced degree (MS/PhD) preferred.

Nice To Haves

Experience with experimentation frameworks (A/B testing, causal inference, uplift modeling).
Familiarity with modern data stacks (dbt, Snowflake, Looker, etc.).
Background supporting high-velocity enterprise or cloud infrastructure GTM teams.

Responsibilities

Partner with Sales, Revenue Operations, Marketing, and Finance to define the data foundation for GTM, including instrumentation, metric definitions, pipelines, dashboards, and reporting.
Design, build, and maintain scalable data models and statistical/ML frameworks (e.g., segmentation, lead scoring, win/loss analysis, churn prediction, propensity modeling).
Transform complex datasets into actionable commercial insights, identifying growth levers, bottlenecks, competitive dynamics, and customer behavior patterns — and convert them into strategic recommendations.
Lead GTM planning cycles: develop forecasting models, scenario planning, “what-if” analyses, target-setting methodologies, and playbooks.
Produce executive-level reporting and communicate insights and recommendations clearly to senior leadership and cross-functional stakeholders.
Partner with data engineering/analytics teams to ensure data integrity, governance, and readiness for advanced analytics; uphold best practices in modeling, documentation, and reproducibility.
Drive experimentation: design A/B tests, pilots, and measurement frameworks for new GTM initiatives, product launches, and sales motions.
Own the end-to-end analytics lifecycle: data collection → modeling → insight generation → strategy → execution → measurement.
Mentor junior data scientists, analytics engineers, and BI professionals; help cultivate a data-driven culture within Sales Operations.