Sr. Data Scientist - Risk & Fraud - AppFolio, Inc
San Diego, CA
About the Job
Hi, We’re AppFolio
We’re innovators, changemakers, and collaborators. We’re more than just a software company – we’re pioneers in cloud and AI who deliver magical experiences that make our customers’ lives easier. We’re revolutionizing how people do business in the real estate industry, and we want your ideas, enthusiasm, and passion to help us keep innovating.
We're looking for an experienced Data Scientist with a strong background in machine learning, data analysis, and software engineering to automate and optimize risk detection processes for online transactions.
Your impact
- Develop and implement advanced risk detection and fraud prevention systems
- Collaborate with Payments cross-functional partners to understand business needs and define key risk indicators
- Identify and surface variables that uncover risky behavior on the platform
- Prototype, deploy, and maintain machine learning models for real-time fraud detection
- Integrate detection algorithms into existing internal tools and workflows
- Conduct ongoing research into emerging fraud techniques and adapt strategies accordingly
- Continuously monitor and optimize system performance to ensure effectiveness against evolving criminal strategies
- Develop comprehensive monitoring and analytical reporting solutions
- Work closely with Risk and Fraud teams to understand emerging trends and reporting needs
- Create tools for monitoring data outliers and trend shifts
- Design and implement dashboards to visualize/investigate customer transaction patterns, account activity, and platform usage
- Develop automated anomaly detection systems to flag unusual behavior
- Build and maintain data pipelines to support real-time reporting and alerting
- Collaborate across teams to analyze and communicate the holistic impact of risk and fraud on the payments business
- Develop customer risk profiles for appropriate transaction handling and approval processes
- Partner with product and business scientists/analysts to quantify fraud's effect on key metrics like customer retention, transaction volume, and revenue
- Assist in creation of comprehensive dashboards linking fraud patterns to overall business performance
- Conduct cross-functional analyses on how fraud detection strategy changes affect various business areas
- Contribute to strategic planning sessions, aligning fraud prevention initiatives with broader business goals
- Contribute to overall Data Science and Analytics infrastructure:
- Develop reusable code libraries and modeling frameworks to support data apps, pipelines, and models across domains
- Implement best practices for version control, documentation, and reproducibility
- Collaborate on building scalable data assets that support both Payments and broader analytics needs
- Participate in knowledge sharing sessions to elevate the team's collective capabilities in rapidly evolving data science technologies and techniques
Qualifications
- Technical skills – should be able to research and implement various advanced analytical techniques needed to manage and scale our Risk & Fraud teams. Candidates should not only have the mathematical background to understand the pros and cons of various techniques, but also the engineering prowess to deploy and manage these models.
- Business acumen – understands key challenges facing our business and partners with key stakeholders to find creative ways to apply data science to solve them; connects dots between data & business outcomes
- Attention to detail – appropriately checks all work for errors and does not let important details slip when it comes to data and its accuracy
- Creative problem solving - able to use creativity and curiosity as tools to pick apart any problem, producing a solution which is relevant and realistic
- Efficiency – able to quickly iterate on data generation and refinement. Looks for ways to improve processes to maximize efficiency and remove redundancy
- Curiosity - always striving to learn more, keeping up to date with the latest tools and techniques being applied in industry.
Must have
- Bachelor’s Degree in a STEM field and minimum 4-6 years experience in a related field
- Strong programming background (Python, SQL, R, etc.)
- Experience working with real-time payments/transactional data
- Experience developing, deploying, and monitoring machine learning models
- Experience creating, managing, and scaling data pipelines for reporting purposes
- Experience using cloud-based technologies and working in collaborative environments with version control
- Listening and interpersonal skills; ability to support, work, and communicate with cross functional partners in both technical and business terms
- Highly self-motivated and directed
- Proven analytical and creative problem-solving abilities
- Ability to effectively prioritize and execute tasks in a high-pressure environment
Nice to Have
- Experience in risk or anomaly assessment/detection
- Experience using dbt (data build tool)
- Experience using orchestration tools such as Airflow, Luigi, Dagster, etc.
- Interest/knowledge working with LLMs
- Experience as a mentor or tech lead on an analytics team
Compensation & Benefits
The base salary/hourly wage that we reasonably expect to pay for this role is: $138,400-$173,000
The actual base salary/hourly wage for this role will be determined by a variety of factors, including but not limited to: the candidate’s skills, education, experience, etc.
Please note that base pay is one important aspect of a compelling Total Rewards package. The base pay range indicated here does not include any additional benefits or bonuses/commissions that you may be eligible for based on your role and/or employment type.
Regular full-time employees are eligible for benefits - see here.
Regular full-time employees are eligible for benefits - see here.
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Source : AppFolio, Inc
