Sr. Data Science Engineer - 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 are looking for a Senior Data Science Engineer to join the Data Science & Analytics Department. You’ll be expected to communicate cross-functionally to support strategic priorities while extracting deep context on who our customers are, what drives their behavior, decision-making, and product adoption, in order to codify that into data models that combine the right dimensions for multi-purpose use cases.
Your impact
Collaborate to structure and derive more value out of our data across acquisition and growth efforts:
- Leverage source of truth MQL opportunity data assets and sales performance metrics to build dbt data models for data scientist use-cases across account scoring, sales forecasting, and headcount planning projects.
- Perform data discovery on GTM analytics reporting logic to identify opportunities and priorities for creating shared business definitions in dbt for our ML efforts.
- Partner cross-functionally to combine or create add-on services enablement to adoption funnel data models to power data science efforts in product upsell customer targeting.
- Collaborate on building scalable data assets that support both marketing/sales objectives and broader analytics needs across our prospects and customer base.
- Help support our competitive intelligence data being actionable/available to power deeper segmentation across our prospect/customer base.
Contribute to Data Science infrastructure and long-term strategy:
- Partner and support multiple GTM data science efforts with efficient ML operations, including parameterized train-test splits, and performance monitoring, and ensure ML model outputs are available in the right data assets for business use-cases.
- Design and enhance dbt data models prospect data, customer and business analytics use cases to eventually power self-serve reporting tools
- Document data sources, metric definitions, and assumptions to drive adoption of curated data assets
- Identify data quality issues and implement semantic data layer standards
Qualifications
- Technical skills – Create and maintain data models, tables, and dashboards needed to manage and scale our Sales and Marketing teams.
- Business acumen – understands key challenges facing our business and partners with key stakeholders to find creative ways to apply data analytics to solve them; connects dots between data & business outcomes
- Attention to detail – Proactively checks all work for errors and does not let important details slip when it comes to data and its accuracy
- Cross-Functional Knowledge: Navigates across verticals and functions and understands how each department contributes to our mission. Able to build relationships and quickly establish trust with others to make things happen. Brings teams and people together to accomplish important things.
- Efficiency – able to quickly iterate on data generation and refinement. Looks for ways to improve processes to maximize efficiency and remove redundancy
Must have
- Minimum of 5+ years of work experience in a technical role, Analytics/Data Engineering or Data Science.
- Full Stack Data Science experience: Demonstrated success in bridging the gap between high-level project requirements and complex application data
- Data engineering: expertise in dbt, object oriented programming, and the technical skills to build and deploy model pipelines to production. Experience creating/editing widely used production tables.
- Data analysis, visualization, and exploration: Exploratory data analysis skills are a critical tool for every full-stack data scientist, and the results help answer important business questions.
- Proficiency in SQL and Python-based (Pandas and/or Spark) approaches for data transformation.
- Communication - You have a wealth of experience helping product teams make great decisions with data.
Compensation & Benefits
The base salary that we reasonably expect to pay for this role is $138,400-$173,000.
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.
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