Data Scientist, Sales Operations & Automation - AppFolio, Inc

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 workforce optimization, machine learning, data analysis, and software engineering to improve the scale and efficiency of our sales and business development operations.

Your impact 

Optimize Sales and Business Development efforts and resource allocation:

• Business Forecasting: Develop and implement data-driven Sales forecasting models and uplevel accuracy by incorporating in-depth workforce capacity inputs, prospect data signals, historical performance trends, and market dynamics. Modeling would include segment and product-level outputs with risk indicators.
• Pipeline Creation: Develop a Sales and Business Development Representative (BDR) pipeline creation forecasting and conversion rate model(s) to assess productivity, progression, and contribution. Modeling would include segment and product-level outputs with risk indicators.
• Account Targeting: Partner to help build and deploy a propensity to buy model per Account (New Business) and Customer (By Product) that can be leveraged across Appfolio for various efforts.  These efforts span Account Tiering, Outreach prioritization (Sales, BDR, or Marketing), and Financial Target Planning
• Capacity / Efficiency: Combine provided propensity-to-buy models with sales workforce efficiency metrics to optimize staffing of BDRs, sales reps, and account managers across tiers, regions, and segments.  Leverage natural language processing techniques on Sales call transcripts and support case data to understand customer sentiment and drive Sales enablement strategy.  Optimize the timing and content of follow-up communications by designing a next-best-action framework for current and potential customers.

Collaborate across teams to drive wider business value:

• Partner with Prospect/Account DS and Marketing analysts to align Sales and Marketing strategies for cohesive customer acquisition.
• Partner with Prospect/Account DS to ingest customer lifetime value prediction models to forecast future revenue and inform business decisions around pricing and packaging.
• Partner with Product DSs/DAs and Product teams to identify opportunities for feature additions/improvements based on Sales data and customer feedback.
• Partner with Product DSs/DAs to align prospect/growth efforts with new features and launches, targeted to focused audiences.
• Assist in quantifying the impact of Sales strategies on key business metrics like revenue growth and customer retention.

Contribute to Data Science & Analytics infrastructure:

• Develop reusable code libraries and modeling frameworks to support data applications across the organization.
• Implement best practices for version control, documentation, and reproducibility in our data science workflows.
• Collaborate on building scalable data assets that support both Sales Operations and broader analytics needs.
• Participate in knowledge sharing sessions to elevate the team's collective capabilities in data science technologies.
• Assist in the evaluation and implementation of new tools and technologies to enhance our data science capabilities

Qualifications 

• Technical skills – should be able to research and implement various advanced analytical techniques needed to manage and scale our Sales Operations 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 2-4 years experience in a related field
• Strong programming background (Python, SQL, R, etc.)
• Experience working with sales/CRM analytics
• 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 working with sales, CRM, or marketing data
• Familiarity with real estate or property management industries
• Experience using dbt (data build tool)
• Experience using orchestration frameworks such as Airflow

Compensation & Benefits

The base salary that we reasonably expect to pay for this role is $108,000-$135,000

The actual base salary 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 that you may be eligible for based on your role and/or employment type.

Regular full-time employees are eligible for benefits - see here.