Sr. Data Scientist

We are looking for an individual to join our Data team who is conversant in data analytics and data science, eager to democratize data by building business centric datasets and passionate about extracting data insights to grow our business.The selected candidate will partner closely with our Revenue Operations team and also directly with founders and leaders in Sales, Marketing & CS leaders as a trusted thought partner. Together, we’re going to tackle a lot of unknown challenges, figure things out, and just #shipit!

You will infuse our business decision making with data and ML-powered insights; and bring a data-driven perspective on growth. You will collaborate with the data and infrastructure teams to evolve our data stack. 

Day in the Life:

A rough estimate of prioritizing time for the role includes:

• GTM Intelligence (50%) - Partner with our GTM and Product teams to drive increasingly sophisticated insights into levers for growth. Potential initiatives include new product & new feature adoption, churn prediction, upsell/cross-sell targeting, customer health scores and forecasting.
• Analytics (30%) - You will take point on our company's analytics ecosystem, including GTM (go-to-market) team, EPD (engineering, product, design) team, and G&A (general and administrative; e.g. finance, etc.) team. At this nexus, you will own the core data modeling and data transformation required to democratize data from disparate systems for our internal users.
• Data Science (20%) - You will partner with our data scientists to architect, build and maintain the data stack for Workstream, and implement ML-powered business analytics. This includes Python programming and building model pipelines with MetaFlow.

Stepping back, this is an opportunity to create a truly data-driven culture across Workstream. One that is cognizant of how to structure rigorous tests, interpret their outcomes, and take clear data driven actions. It's a chance to establish a single source of truth as well as train & mentor colleagues (analysts, ops people, product managers, etc.) on how they can best use data to guide their own work. And an opportunity to build something big.

Who You Are:

• You have 2+ years work experience in GTM data science, with additional 3+ years experience in other data science or data analyst roles in a rapid growth SaaS environment. You have a good sense of what excellent is at +$100M ARR scale and are looking for a chance to build.
• You have demonstrated experience driving change. 
• You possess excellent SQL skills and a fundamental understanding of relational databases and you enjoy creating elegant queries / visualizations.
• You have experience with Snowflake, ETL tools like Airflow and BI tools like Mode, ReDash or Tableau.
• You are proficient in Python and feel comfortable with the common data science stack like Pandas, scikit-learn and NumPy.  
• You are an excellent written and verbal communicator, comfortable communicating technical concepts to high level stakeholders.
• You are able to work effectively in an unstructured environment requiring new perspectives, creative approaches, and multiple competing deadlines. You are unfazed by ambiguity and can adapt quickly to change.

What We Offer:

• A mission-driven and values-based company dedicated to empower deskless workers and local businesses
• An early employee opportunity at a Series B high growth startup; work with the founding team and industry veterans to accelerate your career
• Competitive salary and equity
• Comprehensive health coverage: medical, dental, and vision. We pay 95% of your premiums for our employees and 85% for dependents
• 401K Plan 
• Pre-tax commuter benefits
• Learning/development stipend
• Unlimited PTO
• Hybrid Office/WFH schedule

Salary Range: In compliance with the California Pay Transparency Law, the base salary range for this role is between $150,000 - $200,000 in San Francisco. This range is not inclusive of our discretionary bonus or equity package. When determining a candidate’s compensation, we consider a number of factors including skillset, experience, job scope, and current market data.