Data Scientist

Summary

Candid is a nonprofit providing data and insights about the social sector. The Data Scientist will work as a generalist applied scientist, applying machine learning to data quality, model evaluation, data products, and exploratory prototypes while partnering with product, data, engineering, analytics, and subject-matter teams.

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

Skills

• 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
• Sensitivity and respect for racial, gender, sexual orientation, and cultural differences
• Commitment to Candid's values: driven, direct, accessible, curious, and inclusive
• 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

Qualifications

Must Haves

• 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
• Sensitivity and respect for racial, gender, sexual orientation, and cultural differences
• Commitment to Candid's values: driven, direct, accessible, curious, and inclusive

Nice to Haves

• 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

Benefits

• Health insurance (medical, dental, vision)
• Retirement contribution with additional option for a match
• Paid life insurance and AD&D
• Paid leave time (PTO, compassionate leave, volunteer, holiday, parental)
• Short-term and long-term disability
• Pre-tax transit
• Flexible spending accounts
• Supplemental insurance
• Summer hours
• Public Service Loan Forgiveness (PSLF) program eligible employer
• Remote work arrangement
• 35-hour work week, Monday through Friday