New Data Scientist, Enterprise Analytics

November 6, 2026

Remote

Middle

Canada, United States

Keep in mind

Citizenship requirement applies

Description

The company is hiring a Data Scientist on the Enterprise Analytics team to serve as a trusted analytical partner to Sales, Revenue Operations, and Finance. The role applies statistical, experimentation, and machine learning methods to forecast outcomes and explain what drives activation, conversion, expansion, and retention. It also supports company-level GTM performance reporting covering consumption, ARR, and first orders.

Responsibilities

Embed with business teams as a trusted partner supporting insight generation and strategic decision making across GTM
Perform exploratory data analysis to uncover behavioral trends, long-term patterns, and key drivers behind business performance, communicating impact to non-technical audiences
Build and productionize machine learning models such as propensity, PQL scoring, churn, and expansion models, including training, validation, testing, and feature engineering, using MLOps practices and tooling (CI/CD for ML pipelines, model registries, automated retraining, and monitoring) to move work from notebook to production
Design, run, and evaluate growth experiments (A/B tests and quasi-experiments) on onboarding, pricing and packaging, and upgrade flows
Build and operationalize agentic workflows for analysis, modeling, and pipeline automation, with evaluation and monitoring that keep insights accurate and traceable
Contribute to the Semantic Layer enabling stakeholders and agents to self-serve metrics using trusted and tested sources
Write production-grade Python and SQL meeting internal standards for style, maintainability, and performance, and maintain these standards through code review

Requirements

3-5 years of professional experience in GTM analytics, data science, or a similar technical role
Ability to translate ambiguous business problems into clear, measurable questions and communicate technical concepts to non-technical stakeholders
Experience with experimentation and causal inference (A/B testing, power analysis, quasi-experimental methods)
Experience with statistical and machine learning methods such as regression, classification, clustering, and survival analysis
Deep hands-on understanding of SQL in cloud data warehouses like Snowflake SQL, including product usage and event data
Experience with business intelligence tools (Looker, Tableau, Hex, or similar)
Experience using Python for statistical modeling, machine learning, and production data science, including pandas, NumPy, scikit-learn, Jupyter, LightGBM and XGBoost
Hands-on experience building agentic workflows with AI coding agents such as Claude Code or OpenCode, connecting agents to tools like MLflow and evaluating output for accuracy
Experience working in a B2C company with metrics including Consumption, CRR, ARR, and Churn and Contraction
Self-motivated and self-managing, with strong organizational skills
Ability to thrive in a fully remote organization

Conditions

Benefits to support your health, finances, and well-being
Flexible Paid Time Off
Team Member Resource Groups
Equity Compensation and Employee Stock Purchase Plan
Growth and Development Fund
Parental Leave
All roles are fully remote
Candidates with varying levels of experience are welcome; not every requirement must be met