Sr. Data Science Engineer, Product

AppFolio • San Diego, CA

Company

AppFolio

Location

San Diego, CA

Type

Full Time

Job Description

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 product adoption behavior and their decision-making in order to codify that into data models that combine the right dimensions for multi-purpose use cases.  

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Your impact 
Collaborate to structure and derive more value out of our data across product development efforts:
  • Build Scalable Data Products - Create data models for product adoption metrics and customer performance insights for data science use cases in support of Product Development objectives.
  • Define Shared Business Metrics - Establish data model discovery tools to foster an informed data modeling environment, allowing the department to consolidate model sprawl and achieve consistent, shared business definitions within dbt for more standardized metric use across teams.
  • Keep up with Application data improvements from Product Development - Renovate our dbt environment with new application data to support scalable, reliable data models throughout the organization including the streamlining of Resident journey insights and more.
  • Performance Management - Work through customer performance reporting gaps internally to partner on external product-based solutions in the future. 
Contribute to Data Science infrastructure and long-term strategy:
  • Contribute to data science developer operations and experience by maintaining and optimizing departmental tools, shared data models, workflows, and infrastructure.
  • Support the creation of discovery tooling for data models in dbt.
  • Design and enhance dbt data models for product and business analytics use cases to power self-serve analytics 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 and design principles. 
Qualifications
  • Technical skills – Create and maintain data models, tables, and infrastructure needed to manage and scale our Data Science & Analytics department.
  • 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/Engineering: experience in storing, moving, transforming, analyzing, and presenting data with the ability to understand and solve the types of challenges presented to those working in each part of the data stack
  • Problem Solving & Project Management Skills: Demonstrated success in bridging the gap between high-level project requirements and complex application data
  • Data/Analytics Engineering: expertise in orchestration tools, 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 data science engineers, 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/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.
​​

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Date Posted

12/21/2024

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