Vouch Insurance · 1 day ago
Applied Data Scientist
United States
Full-time
Remote
Mid, Senior LevelVouch Insurance is a tech-enabled insurance advisory and brokerage focused on supporting growing companies in technology and life sciences. They are seeking an Applied Data Scientist to leverage data and AI, particularly large language models, to enhance product features and drive product analytics. The role involves working with real-world data to identify quality issues and improve product decisions based on data insights.
FinanceFinancial ServicesInsuranceInsurTech
Responsibilities
Build and iterate on LLM & AI-powered product features
Design, prototype, and ship features that use LLMs (e.g., content generation, summarization, classification, semantic search, assistants, recommendations)
Work with engineers to integrate LLMs into the product via APIs or internal services (RAG, tools/functions calling, workflows, pipelines)
Define evaluation strategies for LLM features (e.g., human-in-the-loop evaluation, rubrics, prompt experiments, offline/online metrics)
Continuously refine prompts, data pipelines, and system design based on user behavior, quality metrics, and product goals
Own product analytics for data- & AI-powered features
Partner with product managers and designers to define success metrics (e.g., adoption, engagement, conversion, retention, quality, time-to-value)
Instrument new features: define events, ensure proper logging, and validate that data is correct and trustworthy
Analyze funnels, cohorts, user journeys, and experiment results to understand drivers of behavior and outcomes
Translate insights into clear recommendations that influence roadmaps, prioritization, and feature iteration
Work with real-world transactional data (SQL & NoSQL)
Explore, clean, and transform data from transactional (OLTP), analytical (OLAP), and event-based systems
Work across SQL (e.g., Postgres, Snowflake) and NoSQL (e.g., Redis, document/Key-Value stores)
Design data assets and features that are usable by both analytics workflows and LLM/ML systems
Data quality, measurement, and monitoring
Define and track data quality metrics (completeness, consistency, timeliness, drift, schema changes)
Build checks, monitors, and alerts to detect data issues that can affect analytics or AI/LLM performance
Work with data and engineering teams to diagnose root causes and drive changes that improve data quality over time
Applied ML fundamentals
Use core ML concepts (feature design, model evaluation, bias/variance, generalization) to reason about LLM and non-LLM approaches
When appropriate, build and evaluate lighter-weight or traditional models (e.g., scoring, ranking, classification) to complement or replace LLM solutions
Qualification
Required
A track record of high ownership: taking responsibility for problems end-to-end, improving systems rather than just describing them, and pushing initiatives across product, engineering, and data
A genuine love for messy, real-world data, and the curiosity to dig into anomalies until you understand what's really happening
Hands-on experience with real-world transactional data in production environments, including messy, incomplete, or biased data
Demonstrated experience improving data quality in production environments
Demonstrated experience shipping LLM-based product features, such as: Using hosted LLM APIs or in-house models, Designing prompts and workflows, Evaluating and iterating on LLM behavior using real user data
Experience in product analytics, including: Defining and tracking product KPIs and feature-level metrics, Building and interpreting funnels, cohorts, and retention/engagement analyses, Influencing product decisions and roadmaps with data-driven insights
Experience measuring and improving data quality, and working with engineering to fix upstream issues
Strong communication skills: ability to work cross-functionally and explain technical decisions and trade-offs to non-technical partners
Strong SQL skills: complex joins, window functions, CTEs, and performance-aware querying
Solid Python skills for data and AI work (e.g., pandas, NumPy, scikit-learn; OpenAI, Anthropic, and Gemini LLM libraries/frameworks)
Formal education in machine learning concepts, such as: Supervised/unsupervised learning, Model selection and regularization, Evaluation methodologies (train/validation/test splits, cross-validation, experiment design)
Preferred
Experience with LLM tooling and patterns (e.g., RAG, vector databases, prompt/tool orchestration frameworks)
Familiarity with experimentation platforms and A/B testing frameworks
Exposure to MLOps / LLMOps: model versioning, monitoring model & LLM feature performance, feedback loops
Experience with cloud data platforms (AWS, GCP, or Azure) and tools like Snowflake, dbt, or Dagster
Benefits
💰 Competitive compensation and equity packages
⚕️ Health, dental, and vision insurance
🍼 Parental leave
🌴 Flexible vacation time
🪷 Wellness allowance
🛜 Technology allowance
📚 Company-sponsored personal and professional development
🏫 L&D: Partnerships with Ethena and monthly Lunch & Learns
🧘 Wellbeing: access to many wellbeing perks, including Peloton, Fetch, OneMedical, Headspace care+, etc.
🤗 Caregiver Support: company seed into the dependent care FSA and company sponsored Care.com membership.
📊 Regular performance reviews: Vouch conducts regular performance discussions with all team members, offering goal setting and check-ins, development discussions, and promotion opportunities.
Company
Vouch Insurance
Insurance... sounds slow, old-fashioned, and unexciting. Exactly.
Founded in 2018
201-500 employees
H1B Sponsorship
Vouch Insurance has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (3)
2024 (5)
2023 (2)
2022 (2)
2021 (5)
Funding
Current Stage
Late StageTotal Funding
$184.72MKey Investors
Allegis CapitalRibbit CapitalRedpoint
2025-02-13Series D
2024-03-11Series C· $25M
2021-09-10Series C· $60M
Leadership Team
Sam Hodges
Co-founder and CEO
Travis Hedge
Co-Founder and CRO
Recent News
globallegalchronicle.com
2025-09-12
FF News | Fintech Finance
2025-08-13
Company data provided by crunchbase