Staff Data Scientist

### Who you are
- You identify what actually matters in a dataset and why it matters for the business. You ask sharp questions that surface the real problem, connect analytical results to concrete GTM actions, and make sound calls when the data is incomplete
- District GTM data arrives from multiple systems with inconsistent definitions and incomplete coverage. You treat that as a normal constraint. You can debug a messy Salesforce dataset, design robust pipelines despite imperfect inputs, and propose structural fixes when the problem is upstream
- You can take an ambiguous business question and turn it into a structured analytical plan. You design and analyze experiments, apply statistical reasoning to draw conclusions, and build models that improve how decisions get made
- Staff DS at ClassDojo means owning your own infrastructure. You can build and maintain the pipelines, dbt models, and analytical systems your work depends on, and operationalize your analysis without relying on a separate engineer. You know when instrumentation is the bottleneck and can fix it
- You communicate analytical ideas clearly to non-technical audiences, simplify complex data problems into plain explanations, and build enough cross-functional alignment that the analysis actually gets used
- You build frameworks that others can pick up and apply, connecting individual findings to broader GTM strategy. Your work compounds over time rather than sitting in a one-off report
- You have 8+ years in data science or analytics
- You are familiar with SQL and modern analytics tooling (dbt, Redshift / Snowflake / BigQuery)
- You have experience working with CRM systems (Salesforce strongly preferred)
- You have experience analyzing B2B SaaS sales pipeline, funnel, or revenue operations data
- You have a track record of producing data work that changed how a team made decisions
- You have experience working alongside GTM or product teams as a peer
- You have experience in a startup or high-growth environment
- You are familiar with experimentation design and analysis in a GTM context
- You have exposure to product analytics alongside sales data
- You have background in education technology or mission-driven organizations

### What the job involves
- As a Staff Data Scientist embedded with our District GTM team, you'll own the analytical work supporting ClassDojo's district growth. You'll work directly with Sales, Marketing, and Product leadership to build the systems, find the insights, and inform the decisions that move the business forward
- The scope runs from raw CRM and product usage data through to the recommendations that shape how we sell, market, and prioritize. You'll build the infrastructure your work depends on, define what good data looks like, and make sure the analysis actually reaches decisions
- At ClassDojo, Staff means setting the direction. You'll have real influence over how the GTM team operates, with leadership treating you as a peer
- Build a pipeline analytics system the GTM team can use on their own
- Today, our district sales org has multiple competing sources of truth (CRM, product usage, and marketing signals) and relies on ad hoc analysis to answer basic pipeline questions. The goal is a single reliable reporting model that integrates all three data sources, standardized GTM metrics, and self-serve dashboards that let Sales check pipeline health without filing a data request
- Make data a genuine input to GTM decisions
- You'll identify the key drivers of pipeline conversion (e.g. teacher adoption signals, district size, persona engagement), build models that predict deal likelihood, and run structured experiments with Sales and Marketing that measurably change how the team operates. In 18 months, GTM leadership will reach for data first when making targeting, messaging, and prioritization calls
- Make core B2B datasets reliable enough to build on
- CRM, marketing, and product datasets arrive fragmented and inconsistently defined. You'll clean and structure them into stable analytical models with documented definitions, identify instrumentation gaps and resolve them with engineering, and create a foundation where new GTM analytics workstreams can be stood up quickly
- Work alongside District GTM leadership as a trusted analytical partner
- You'll regularly work with District GTM leadership as they frame key business questions and weigh tradeoffs. You'll translate ambiguous problems into clear analytical approaches, communicate findings directly, and inform long-term decisions about how and where we grow
- Our stack includes the following technologies: Salesforce (CRM) · SQL · dbt · Amazon Redshift · Metabase · Airflow · GitHub

### Benefits
- Work from home opportunities