Principal Data Scientist

Job Summary

We are looking for a hands-on Data Scientist with a strong statistics and AI foundation to work across raw, unstructured, and behavioral data - engineering features, building advanced models, and shipping production-grade deliverables in close collaboration with the clients data and engineering teams.

Responsibilities

• Mine raw credit bureau (tradeline-level) and bank transaction data to identify, structure, and validate discrete, machine-readable risk signals with clear trigger conditions and supporting evidence.
• Apply LLM-based extraction techniques to convert unstructured data (e.g., sales call transcripts) into structured, schema-validated signals (claim credibility, objection type/resolution, sentiment) suitable for downstream models - not narrative summaries.
• Engineer features from high-frequency, noisy behavioral/interaction event data using sequence and trajectory analysis, clustering, and state-based modeling.
• Build and validate advanced models spanning classical ML, survival/hazard modeling (Cox, parametric, ML survival models), and Bayesian methods (hierarchical models, empirical Bayes, sequential updating).
• Rigorously test whether new signals/features add incremental predictive value beyond existing structured models - avoid replicating what current models already capture.
• Take models and features from experimentation through to production-grade deliverables: version-controlled code, reproducible pipelines, and monitored production services.
• Own Python codebases with GitHub-based version control and CI/CD workflows for feature/model deployment.
• Contribute reusable content, frameworks, and learnings to Affines internal AI Center of Excellence (CoE).
• Operate entirely within access-controlled infrastructure, working only with de-identified data under named-user access.

Job Type

Full-time

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