Your role as a Data Scientist is to support stakeholders through data science techniques and building the solutions for the business’s key initiatives. In addition, you will leverage PandaDoc’s data to enhance business performance and help stakeholders achieve their goals. You will be assisting the business to continue its evolution into a data-driven culture and will apply and inspire the adoption of advanced data science across the business.
You will report to the Director of GTM Analytics and work closely with the Marketing, Sales, and Customer Success organizations. As a Data Scientist, you will take full ownership of your projects from start to finish. This includes collaborating with stakeholders to understand key business questions, sourcing and preparing data, performing exploratory data analysis, building and fine-tuning models, and conducting in-depth analysis. You will communicate your findings and insights through dashboards, visualizations, and presentations, ensuring alignment with business objectives.
In this role, you will:
- Use data and apply creative analytical problem-solving skills to a wide variety of sales/marketing questions to deepen our understanding of campaign & funnel effectiveness, customer journeys, and go-to-market performance
- 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
- Example projects would include:
- Analyze how prospects and customers navigate our marketing websites and identify opportunities for improved engagement and conversion
- Build Lead/Account scoring models and customer health models
- Investigate root causes for customer churn, contraction, and expansion and develop predictive models and prescriptive programs to improve profitability
- Determine Ideal Customer Profile (ICP), key personas, and applicable marketing segments to support ongoing enrichment and other campaigns
- Provide a recommendation system for upsell opportunities for our existing customer base
- Manage and enhance our existing customer health model
About you:
- 5+ 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
- 5+ 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)
- 2+ years of MLOps delivery experience
- 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)
- MLOps delivery tool such as Airflow preferred
- Data pipeline and workflow management tools, such as dbt is helpful
It would be awesome if you had but not a must:
- Experience in B2B;
- Advanced degree e.g. Masters;
Company Overview:
PandaDoc empowers more than 60,000 growing organisations to thrive by taking the work out of document workflow. PandaDoc provides an all-in-one document workflow automation platform that helps fast scaling teams accelerate the ability to create, manage, and sign digital documents including proposals, quotes, contracts, and more. For more information, please visit https://www.pandadoc.com.
Company Culture:
We're known for our work-life balance, kind co-workers, & creative virtual team-bonding events. And although our Pandas are located across the globe, we stay connected with the help of technology and ensure that everyone on our team feels, well, like a team.
Pandas work best when they're happy. We retain our talent by upholding our values of integrity & transparency, and selling a product that changes the lives of our customers.
Check out our LinkedIn to learn more.
Benefits:
Our benefits include tremendous career growth opportunities, health and commuter benefits, company paid life & disability, 20+ PTO days, 401K and FSA plans, and of course, a fun team of Pandas to work with! This is a 100% remote role and we are a remote first company.
The compensation range for this position is $140,000 - $170,000 USD plus equity.
PandaDoc is an Equal Opportunity Employer. We are committed to equal treatment of all employees without regard to race, national origin, religion, gender, age, sexual orientation, veteran status, physical or mental disability or other basis protected by law.
EXTERNAL RECRUITERS
Approval Requirement
The use of external recruiters/staffing agencies requires prior approval from our HR Team. The HR Team at PandaDoc requests that external recruiters/staffing agencies not to contact PandaDoc employees directly in an attempt to present candidates. Complying with this request will be a factor in determining future professional relationships with PandaDoc.
