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# Sr. Data Scientist, Forward-Deployed

- **Company:** The Ladders
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $168,349.0 - $230,912.0
- **Contract:** Permanent contract
- **Skills:** Software as a Service, Customer Data Management, Python (Programming Language), SQL Databases, Tableau (Software)
- **Published:** November 5, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pwttlno9d5

## About the Role

* 5+ years of experience in data science or advanced analytics with a focus on business outcomes.
 * Proficiency in SQL and Python, with the ability to transform messy data into reliable analysis.
 * Strong foundation in statistics and experimental design, including control groups and baselines.
 * Experience building dashboards or reporting for business stakeholders.
 * Excellent communication skills with the ability to convey data insights clearly.
 * Ability to manage multiple projects simultaneously.
 * Familiarity with B2B go-to-market or SaaS customer data is a plus.
 * Consulting experience and BI tools such as Tableau are a plus.

## Description

This role is focused on turning complex customer and business data into clear, decision-ready insights that improve engagement outcomes and support commercial performance. You will work closely with senior data scientists and business stakeholders to evaluate model impact, validate account-level analyses, and refine tools used in live customer engagements. The work blends rigorous statistical analysis, experimentation, and dashboarding with a strong emphasis on measurable business value., * Establish baselines for customer engagement metrics and track key outcomes such as account health and renewal performance.

 * Analyze performance differences between scored and unscored accounts, with attention to close rates and deal sizes.
 * Evaluate the impact of model changes on performance and pipeline timing.
 * Conduct analyses that distinguish meaningful effects from noise in the data.
 * Collaborate with senior data scientists on live engagements to validate account lists and refine models.
 * Develop on-demand analysis tools that support customer insights and engagement outcomes.
 * Create dashboards and reports for stakeholders to monitor engagement results.