Applied AI, Data Scientist

Knights of Columbus

Applied AI & Data Scientist developing machine learning and generative AI solutions for Knights of Columbus' core operations. Collaborating with various teams to deliver impactful results.

Posted 5/29/2026full-timeNew Haven • Connecticut • 🇺🇸 United StatesMid-LevelSenior💰 $98,000 - $166,500 per yearWebsite

Tech Stack

Tools & technologies

CloudFlaskNumpyPandasPostgresPythonScikit-LearnSQL

About the role

Key responsibilities & impact

Support end-to-end delivery of AI solutions: participate in problem framing, exploratory analysis, model development, and measurement of outcomes
Develop and validate machine learning models under guidance (e.g., classification/regression, time series, anomaly detection, NLP as appropriate)
Contribute to GenAI solutions by building and improving Retrieval-Augmented Generation (RAG) components (document preparation, chunking, metadata, and retrieval testing) and prompt templates following established patterns
Perform data analysis and feature engineering: data quality checks, joins, transformations, leakage checks, and creation of reusable features
Define and track model/LLM quality metrics with support (e.g., accuracy, calibration, stability; groundedness/factuality for LLM outputs), and help maintain evaluation datasets and test cases
Assist with explainability and documentation: summarize model behavior, limitations, and key drivers; contribute to model cards and audit-ready artifacts
Work with data engineers and platform teams to operationalize solutions: support pipeline integration, scheduling, monitoring, and troubleshooting
Apply responsible AI practices: follow privacy/security requirements, handle sensitive data appropriately, and participate in bias/fairness reviews
Communicate findings clearly: prepare concise readouts, visuals, and recommendations for technical and non-technical audiences

Requirements

What you’ll need

3+ years of experience (or equivalent) in data science, analytics, or applied machine learning with demonstrated project delivery
Strong foundation in statistics and predictive modeling; ability to design validation approaches and interpret results
Proficiency in Python and SQL; experience with common data science libraries (pandas, NumPy, scikit-learn) and version control (Git)
Experience working with cloud data platforms and relational databases; familiarity with Snowflake and/or PostgreSQL strongly preferred
Familiarity with machine learning lifecycle concepts: training/validation splits, feature engineering, reproducibility, and basic monitoring metrics
Ability to communicate clearly and collaborate in cross-functional teams
Hands-on exposure to GenAI/LLM solutions (prompting, embeddings, retrieval/RAG, or evaluation) through work projects or applied learning (preferred)
Experience with visualization and storytelling tools (e.g., Power BI) to communicate insights (preferred)
Familiarity with ML/LLM evaluation practices (test sets, error analysis, human review, groundedness checks) (preferred)
Experience with basic software engineering practices (unit testing, packaging) and/or API integration (FastAPI/Flask) (preferred)
Financial services experience or experience in regulated environments (model documentation, audit readiness, privacy/security constraints) (preferred)

Benefits

Comp & perks

13 paid holidays per year in addition to vacation and paid sick leave
Flexible workweek schedules
Certifications, designation, and tuition reimbursement
401(k) retirement savings plan with matching company contributions
Cash balance retirement plans fully funded by the company
Short-term disability and term life insurance fully paid for by the company
Up to 12 weeks of childbirth leave under STD policy
One week of fully paid parental leave for all new parents, including adoptive and foster parents
A variety of health insurance options, including premium-level family coverage
Pre-tax Health Savings Account with employer contributions
Long-term disability insurance
Dental insurance
Vision insurance
Health club membership reimbursement
Employee Assistance Program

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningdata analysisfeature engineeringpredictive modelingPythonSQLpandasNumPyscikit-learnGenAI

Soft Skills

communicationcollaborationproblem framingexploratory analysisdocumentationexplainabilityconcise readoutsvisual storytelling