> Markdown version of [/jobs/ext/4601059-sr-data-scientist](https://www.wearedevelopers.com/jobs/ext/4601059-sr-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data Scientist - **Company:** AppFolio, Inc. - **Location:** Goleta, CA, United States - **Experience:** Expert - **Salary:** $138,400.0 - $173,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Cloud Database, Code Generation, Code Review, Computer Programming, Data Presentation, Relational Databases, Python (Programming Language), Operational Databases, SQL Databases, Workflow Management Systems, Usage Analysis, Delivery Pipeline, Claude Code, Snowflake, AI Coding Agents, Agentic-AI, Model Context Protocol, Streamlit Framework, Data Pipelines - **Published:** November 6, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=7692ffca5cca83d5 ## About the Role * Demonstrated success partnering cross-functionally with Product, Engineering, Design and Business leaders to translate analytical findings into strategic product decisions. * Deep expertise in user behavioral data, cohort retention modeling, conversion funnel optimization, and designing complex A/B or causal experiments. * Hands-on experience building, transforming, and validating production data pipelines and creating centralized metric layers. * Proven experience building interactive decision apps, dashboards, or reporting workflows using modern stacks (Hex, Streamlit, Quarto, or comparable data app frameworks). * Familiarity with data modeling tools like dbt, and experience working in dual-sided marketplaces, consumer workflow software, B2B2C, FinTech/InsurTech, or PropTech environments is a plus., * 6+ years of data team experience specializing in product analytics, user behavioral data, and statistical analysis. * Advanced proficiency in SQL and strong programming skills in Python and/or R, with deep familiarity querying relational database structures and cloud data warehouses (Snowflake preferred). * Proven track record designing, analyzing, and scaling A/B testing and causal inference frameworks. * Demonstrated hands-on use of AI coding agents and agentic developer workflows (e.g., Claude Code, Model Context Protocol integrations, or custom skills) to accelerate analyses and automate data workflows, paired with a disciplined framework for auditing and validating AI-generated code. * Strong executive communication and data storytelling skills, with the ability to distill complex statistical concepts into clear insights for technical and non-technical stakeholders., * Data modeling experience using dbt * Experience building data pipelines, tooling, or automation * Experience in one or more of the following: * B2C marketplaces * Customer workflow products (customer input data) * B2B SaaS products * Marketing software products * Real estate sector or PropTech (specifically around resident benefits, insurance, or rewards) ## Description * Optimize the resident journey: Map, measure, and refine end-to-end enrollment and purchase funnels to drive measurable adoption of resident insurance, rewards, and benefit offerings. * Scale experimentation rigor: Build and implement standard causal inference and A/B testing frameworks that validate product hypotheses originated by both product teams and AI agents. * Drive retention & sustained engagement: Develop user behavioral segmentation models to uncover product-market fit signals, curb cancellations, and lift insurance renewal and benefit utilization rates. * Accelerate analytical velocity with AI: Integrate modern AI developer workflows (such as agentic coding assistants and pipeline automation) into team operations while establishing rigorous auditing and QA practices. * Build reusable data assets: Architect standard metric layers and cross-product analytical frameworks that serve as single sources of truth for resident adoption and financial metrics. * Multiply team capabilities: Elevate data science standards across the organization through active design/code reviews, technical mentorship, and knowledge sharing on complex statistical problems.