Lead Data Scientist

Summary

Join PandaDoc as a Lead Data Scientist and leverage data science techniques to build solutions for key business initiatives. You will enhance business performance, foster a data-driven culture, and apply advanced data science across the organization. Reporting to the Director of Product & Growth Analytics, you will collaborate with various teams, own projects from start to finish, and communicate findings through visualizations and presentations. This role requires strong analytical and communication skills, experience with large datasets, and proficiency in various data science tools. PandaDoc offers a competitive salary, comprehensive benefits, and a collaborative work environment.

Requirements

• 7+ years hands-on professional experience in analytics working with large, complex, and multifaceted data sets and applying machine learning science techniques to solve practical business problems
• 7+ years of experience working with cleaning, manipulating, and visualizing data you can extract from multiple sources and an established data warehouse (Snowflake, Redshift, Oracle, Postgres, etc)
• Have a focus on creating repeatable work for models that are not unnecessarily complex
• Comfortable managing multiple projects, competing priorities, and an evolving roadmap
• Excellent communication and presentation skills and proven ability to translate data into actionable insights
• Excellent interpersonal skills, with a consistent record of working across and communicating with all levels of the organization
• Team player who understands the collaborative nature of this work with the ability to influence at C-suite level in a cross-functional environment
• B.A. or B.S. in Mathematics, Statistics, Economics, Computer Science, Engineering Sciences or related discipline
• Experience using the following software/tools: Relational Databases, including Postgres and Snowflake
• R or Python experience with related data science packages (SciKit-Learn, numpy, pandas (duh), Matplotlib)
• Visualization tool (Tableau, PowerBI, Domo, Qlik, etc)

Responsibilities

• Use data and apply creative analytical problem-solving skills to a wide variety of product questions to deepen our understanding of customer workflows, churn risk, and long-term value
• Develop statistical models, machine learning algorithms, process automations, and predictive analytics solutions to address business challenges
• Design experiments to test hypotheses and apply advanced statistical techniques and causal inference methods (i.e. A/B testing, statistical tests, Bayesian experimentation, etc.) to assess effectiveness of proposed changes
• Assist the business and management team in the decision making process using data analysis to make actionable recommendations
• Understand business strategy and high-level roadmap and align analysis efforts to enable them with data insights and help achieve their strategic goals
• Craft, deliver and own performance monitoring dashboards that guide understanding of how the business is performing today and where it may go next
• Work with the data engineering team to get data pipeline processes productionized and automated
• Research and analyze different segments of our customer base to determine better product offering strategies
• Develop a feature recommendation model to be deployed in product
• Build predictive models focused on account adoption and expansion allowing us to improve customer experience, profitability, and forecasting

Preferred Qualifications

• Experience in B2B
• Advanced degree e.g. Masters
• Data pipeline and workflow management tools, such as dbt is helpful

Benefits

• Tremendous career growth opportunities
• A competitive salary
• Health and commuter benefits
• Company paid life & disability
• 20+ PTO days
• 401K and FSA plans
• A fun team of Pandas to work with