Senior Data Scientist

Cribl

23h•Remote

About The Position

Cribl is hiring a Senior Data Scientist to join and grow our internal data science practice. In this role, you'll use predictive models and advanced analytics to give stakeholders clear foresight into what's likely to happen and what to do next. This role is embedded in our centralized data organization, reporting to our Staff Data Scientist, partnering closely with teams like Finance, GTM, and People. You'll turn rich data sets into forward-looking insights that guide planning, business strategy, and execution, and you'll contribute to the technical standards and culture that make our "Foresight First" vision a reality. We pride ourselves on fostering a collaborative and innovative culture where team members enjoy working together - whether remotely or over a meal at a foodie hot spot. If you're someone who thrives in an entrepreneurial environment and is eager to contribute to a company poised for legendary success in the tech industry, we want to hear from you!

Requirements

5+ years of experience in data science or applied statistics with a track record of driving data science projects with meaningful business impact at a software company.
Strong background in experiment design, causal inference, predictive modeling, and ability to distinguish signal vs noise.
Advanced SQL and Python skills, with experience working on large, messy, multi-source datasets within a modern data stack such as cloud data warehouses and transformation frameworks.
Proven ownership of end-to-end data science and ML solutions, from problem framing and data preparation through modeling, validation, deployment to production in partnership with Data Engineering, and ongoing monitoring.
Ability to work effectively in ambiguous, fast-changing environments, navigating from problem framing through implementation and iteration.
Excellent communication, including the ability to present complex findings to non-technical audiences and contribute to strategic decisions
Familiarity with AI-assisted workflows, including leveraging LLMs as tools to accelerate analysis, surface insights, or augment modeling work.

Responsibilities

Own end-to-end data science initiatives that translate ambiguous business questions into clear analytical and modeling problems, from scoping through implementation.
Build, operationalize, and continuously improve machine learning models in partnership with Data Engineering to ensure scalable training & evaluation workflows in production.
Evaluate and interpret the performance of ML models (e.g., classification, recommendation), helping the team reason through trade-offs, limitations, and business implications of model-driven decisions.
Conduct deep-dive analyses using advanced statistical methods to surface actionable insights to stakeholders and positively influence org-wide decision quality.
Apply statistical modeling, experimentation, and AI-assisted analytics to expand how Cribl uses data to answer challenging questions.
Communicate findings clearly and persuasively to executives and cross-functional stakeholders to influence strategic decision-making.
Contribute to technical best practices and team standards, and provide mentorship to junior team members as the practice grows.
Partner closely with Data Engineering, Analytics, and Governance to define data requirements, improve data quality, and ensure the team can efficiently generate trustworthy insights.