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Solvable · 1 week ago

Sr. AI Data Scientist

United States

Full-time

Remote

Mid, Senior Level

$130K/yr - $175K/yr

4+ years exp

Solvable is rebuilding how Americans discover, evaluate, and access insurance. They are seeking a Senior AI Data Scientist to serve as the intelligence engine behind their marketplace, media, pricing, and monetization strategy, focusing on anticipating and modeling decisions to improve performance.

AdviceConsultingLegalProfessional Services

Hiring Manager

Wade Schlosser

Responsibilities

Define and execute Solvable’s data and intelligence strategy in close partnership with Product, Engineering, and Media

Build analyses that move from observation → hypothesis → recommendation → action

Use LLMs, predictive modeling, and anomaly detection to accelerate root-cause analysis and insight velocity

Collaborate with Product to operationalize insights into routing logic, experimentation frameworks, and automated decision systems

Lead weekly performance and intelligence reviews with senior leadership

Translate complex data into crisp, confident recommendations that shape strategy

Proactively identify risks, opportunities, and inflection points before they show up in P&L results

Qualification

Data SciencePredictive ModelingMachine LearningPythonBigQuerySnowflakeDatabricksA/B TestingLLMsAnalytical SkillsCollaborationCommunication

Required

4–8+ years in data science, product analytics, growth analytics, or decision intelligence roles in high-velocity environments (marketplaces, performance marketing, DTC, fintech, or similar)

Demonstrated track record operating as a decision partner, not a reporting function

Strong command of descriptive, diagnostic, predictive, and prescriptive analytics

Advanced proficiency with modern data warehouses (BigQuery, Snowflake, Databricks) and Python for modeling and analysis

Hands-on experience applying ML-informed techniques such as regression, classification, uplift modeling, forecasting, and pricing sensitivity analysis

Practical experience connecting experimentation (A/B, multivariate, Bayesian) to business outcomes

You use AI as a default interface, not a novelty

Experience leveraging LLMs (OpenAI, Claude) for exploratory analysis, anomaly detection, summarization, and pattern discovery

Familiarity with agentic or semi-agentic workflows (LangChain, tool-based orchestration, automated diagnostics)

Comfort building systems where insights surface automatically, not only when someone asks