Applied Data Scientist III

Overview

The expected salary range for this position is $ - $. Employees in specific high cost of labor locations in the United States (such as San Francisco, CA and Seattle, WA) may qualify for a geographic differential.

We’re seeking an Applied Data Scientist III to turn our backlog of AI use cases into scalable, production‑ready solutions. This role is both hands‑on technical and strategy, combining model development, system design, and operationalization in AWS alongside AI adoption and domain readiness. You’ll work to standardize efforts, drive measurable business impact, and elevate data science best practices across the team and enterprise.

You’ll also represent AI platform capabilities to neighboring groups, translating complex ideas and needs into clear value for both non‑technical and technical stakeholders.

• Develop, analyze, and model operational, program, marketing, or other organizational data to analyze the competitive performance of Compassion's business segments.
• Develop innovative strategies, quantify the competitive performance of the organization's operations and/or markets.
• Further evaluate potential operational changes, design new approaches and data methodologies accordingly.
• Perform exploratory data analysis to understand relationships, opportunities to influence outcomes, and how to attribute cross‑channel outcomes.
• Further develop proofs of concept to verify ideas and close the loop to ensure that the proposed solution performs as it should and is correctly understood by clients.
• Translate complex analytical and technical concepts for non‑technical team members to enable understanding and drive informed business decisions and AI adoption.

• Demonstrated ability to act as an AI evangelist—guiding non‑technical teams, influencing adoption, and promoting best practices across the organization.
• Strong ability to quantify impact, including cost savings, ROI, and prioritization of high‑value use cases.
• Experience partnering with business stakeholders and translating technical concepts into clear, actionable items and insights.
• Strong hands‑on experience building and deploying machine learning models end‑to‑end in production environments.
• Proven ability to perform exploratory data analysis and select appropriate algorithms based on business outcomes and data characteristics.
• Hands‑on experience with AWS (especially Sage Maker) for model development, deployment, and orchestration.
• Experience working with modern data platforms such as Snowflake and enterprise data warehouses.
• Ability to consolidate and operationalize multiple siloed use cases into standardized, scalable solutions.
• Seven years relevant experience working in the data field.

• Generous paid time off.
• 10% contribution to a 403(b) retirement fund on top of your salary.
• Excellent health care coverage.
• Free short‑term professional counseling.
• Additional benefits may be offered.