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# Manager, Applied Data Science

- **Company:** AppFolio, Inc.
- **Location:** Chicago, IL, United States
- **Experience:** Experienced
- **Salary:** $167,200.0 - $209,000.0
- **Contract:** Permanent contract
- **Skills:** Sql Data Warehouse, Artificial Intelligence, Airflow, Audit Trail, Software as a Service, Customer Data Management, Data Mart, Data Security, Data Sharing, Python (Programming Language), Machine Learning, Recommender Systems, Salesforce.Com, SQL Databases, Large Language Models, Snowflake, Software Version Control
- **Published:** November 7, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=13eb2037058c7b5e

## About the Role

* Bachelor's degree in a STEM field and 8+ years building and deploying predictive models in production for business stakeholders, including sales, marketing, or customer success teams.
 * 2+ years leading data scientists, as a people manager or as the technical lead who set direction, reviewed the work, and coached the people doing it.
 * Strong programming background, with Python and SQL required. You have taken models you built from raw tables to production yourself and expect to keep building alongside your team.
 * Experience developing, deploying, monitoring, and retraining classification and propensity models end to end, bonus points for designing next-best-action or recommendation systems that arbitrate across several models.
 * Experimental design fundamentals, including holdouts, control groups, power, and honest measurement of incremental lift rather than model accuracy alone.
 * Experience building and evaluating LLM-based products in production, such as agents or natural-language analytics, including the accuracy and coverage checks that gate their use.
 * Experience with a cloud data warehouse such as Snowflake, dbt, an orchestration framework such as Airflow, version control, and CRM data such as Salesforce.
 * A record of setting priorities with senior leadership: turning ambiguous questions into repeatable models, communicating recommendations they act on, and saying no when the data does not support the ask.

## Description

As the Manager, Applied Data Science on our Platform Data Science team, you will lead the Data Scientists who build AppFolio's AI and machine learning products for the business: Our signal engine that turns product usage, account health, and customer interactions into Next Best Actions per persona in GTM teams; Chat-to-Data, our natural-language analytics product; and the forecasting automations our Finance and Customer Success teams plan against. You will be a player-coach. In your first year you build alongside your team to learn our business, our data, and how to coach each person, then shift from doing the work to directing it. This role bridges applied machine learning and SaaS go-to-(vertical)market strategy.

Your Impact

 * Own signal modeling and scoring logic for all of AppFolio's products, and co-create the Next Best Action layer for GTM teams that gives each account ranked recommendations per persona
 * Own shared data science services for the business, forecasting automations, agentic data access and partner with the business to ensure adoption and explainability.
 * Own coding standards for the Cerberus model fleet: coding standards, review gates, deployment, monitoring, retraining, and outputs published to the governed Data Marts with the access controls and audit logging the Business Data Platform requires.
 * Review every pull request and deliverable the team ships, and own the quality and risk of its models, analyses, recommendations and automations.
 * Coordinate delivery with Sales, Marketing, Customer Success, and Finance leaders: set priorities with them, hold Data Science & Analytics' seat on the cross functional working groups, and run the team's operating rhythm so that urgent requests and the roadmap both get delivered.
 * Set the direction for applied AI/ML in Data Science & Analytics with department leadership.
 * Manage and grow a team of Data Scientists: 1:1s, coaching, performance reviews, hiring, and a growth path for each person.