Data Scientist

Data; Northern (KY); Hybrid; USD 100,000 - 140,000; Full time

Job summary

Candid is a nonprofit data and insights leader seeking a resourceful Data Scientist to join the Data Science team. The role spans data-quality fixes at scale, production model evaluation, and prototype data products in collaboration with engineers and PMs.

You will work across ML tasks, embeddings, and semantic search while building dashboards and tools to empower analysts and stakeholders. Strong Python/SQL, production experience, and nonprofit familiarity are preferred.

Qualifications

• 3-5+ years of relevant experience in data science or similar roles.
• Strong Python and SQL skills with experience in production workloads.
• Experience measuring model performance on real-world data, and detecting drift.
• Comfort building dashboards to surface data-quality and model-performance metrics.
• Excellent communication and ability to work embedded in cross-functional teams.

Responsibilities

• Apply ML across data problems including detection, classification, entity resolution, and feature engineering.
• Measure model performance in production and establish ground-truth where labels don’t exist.
• Improve data quality by identifying at-scale errors and routing fixes to owners.
• Prototype solutions and provide clear recommendations for go/no-go decisions.
• Build enabling tooling and dashboards to help analysts and stewards.

Skills

Python

SQL

AWS

Data quality

Model evaluation

Dashboarding

Communication

Team collaboration

Statistical judgment

Tools

Starburst/Trino

Snowflake

Streamlit

Job description

Candid is a nonprofit that provides the most comprehensive data and insights about the social sector. We get you the information you need to do good. Candid currently has an opportunity for a Data Scientist. Candid (candid.org), the nation’s leading authority on philanthropy, seeks a resourceful, creative, conscientious, and detail-oriented data scientist to join the Candid Data Science team. This is a generalist applied-science role, spanning work that ranges from finding and fixing data-quality problems at scale, to measuring how well our models perform in production, to exploring and prototyping new data products and derived fields. Data scientists at this level work fairly independently on project-defined scope, often embedded with a product or data team, and partner with engineers, analysts, PMs, and subject-matter experts. We hire for a broad set of skills and deploy data scientists where they are most needed as priorities shift.

Responsibilities

• Apply ML across data problems: detection, classification, entity resolution and matching evaluation, anomaly detection, embeddings and semantic search, and feature engineering.
• Measure how models perform on real production data (not just test sets), build ground-truth where labels don’t exist, and detect drift and degradation.
• Apply ML to data quality: find systematic, at-scale errors that queries and manual review miss, and route findings to the people who own the fixes.
• Take open-ended questions through to a prototype and a clear recommendation, including ruling ideas out when they aren’t worth building.
• Build enabling tooling and dashboards (for example, semantic search over text, or Streamlit dashboards) that help analysts and stewards do their work.
• Work embedded with a product or data team on project-defined scope, partnering with engineers, analysts, PMs, and subject-matter experts.
• Take on other ML and data-science projects as Candid’s needs and priorities shift.

Skillset

• 3-5 years of relevant experience.
• A strong generalist applied data scientist, comfortable moving across classification, entity-resolution and matching evaluation, anomaly detection, embeddings and semantic search, feature engineering, and exploratory feasibility work.
• Strong Python and SQL, comfortable with large production datasets (Starburst/Trino, Snowflake) and working in AWS.
• Experience measuring model performance on real-world / production data (not just test sets), including building ground-truth where labels don’t exist, and detecting drift.
• Comfort building and maintaining dashboards (the team’s are in Streamlit) that surface data-quality and model-performance metrics.
• Experience taking a fuzzy question to a prototype and a recommendation, and being willing to rule an idea out.
• Sound statistical judgment: sampling, error rates, uncertainty, and knowing when a finding is real.
• Strong communication and comfort working embedded in another team with project-defined scope.
• Preferred someone with experience applying ML to data quality, such as detection or classification models that flag anomalous or wrong records at scale.
• Preferred (any of these are a plus): embeddings, semantic search, or NLP over text corpora; recommendation, ranking, or propensity modeling; computer vision or multimodal ML for image-based QA; experience evaluating entity-resolution or deduplication systems; turning exploration into derived-data products; and familiarity with the U.S. nonprofit and philanthropic sector.
• Willingness to perform other duties and special projects as needed/requested.
• Sensitivity and respect for racial, gender, sexual orientation, and cultural differences.
• Champions and represents Candid’s core values: We’re driven, direct, accessible, curious, and inclusive.

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