- Страна
- США
- Зарплата
- 174 500 $ – 245 000 $
Откликайтесь
на вакансии с ИИ

Staff Data Scientist, District GTM
Высокая оценка обусловлена сильной миссией компании, прозрачной и конкурентной заработной платой, а также высокой степенью влияния на продукт. Работа в распределенной команде с экспертами из топовых тех-гигантов предлагает отличные возможности для профессионального роста.
Сложность вакансии
Роль уровня Staff требует не только глубоких технических знаний (SQL, dbt, Redshift), но и высокого уровня бизнес-интуиции. Кандидат должен уметь самостоятельно строить инфраструктуру данных и влиять на стратегические решения GTM-команды.
Анализ зарплаты
Предлагаемая зарплата ($174k - $245k) находится на верхнем пределе рыночных ожиданий для Staff-позиций в США, особенно учитывая возможность удаленной работы из любого штата. Это подчеркивает стремление компании нанимать таланты высшего уровня.
Сопроводительное письмо
I am writing to express my strong interest in the Staff Data Scientist position for the District GTM team at ClassDojo. With over 8 years of experience in data science and a deep focus on B2B SaaS analytics, I have a proven track record of transforming fragmented data into unified, actionable insights. My background in building robust dbt pipelines and integrating complex Salesforce datasets aligns perfectly with your goal of creating a single source of truth for the district sales organization.
In my previous roles, I have acted as a strategic partner to GTM leadership, moving beyond simple reporting to identifying key drivers of pipeline conversion and deal likelihood. I am particularly drawn to ClassDojo’s mission-driven approach and the challenge of scaling educational impact through data-informed decisions. I am confident that my technical fluency in the modern data stack and my ability to communicate complex findings to non-technical stakeholders will allow me to make an immediate impact on your GTM strategy.
Составьте идеальное письмо к вакансии с ИИ-агентом

Откликнитесь в ClassDojo уже сейчас
Присоединяйтесь к ClassDojo, чтобы определять будущее образования, используя данные для масштабирования платформы, которой доверяют миллионы семей по всему миру.
Описание вакансии
ClassDojo's goal is to give every child on Earth an education they love.
We started by building a powerful network for communication. ClassDojo’s flagship app is the #1 communication app connecting K-12 teachers, children, and families globally. Teachers use it to share what’s happening throughout the day through photos, videos, and messages that make parents feel like they’re there. It’s actively used in over 95% of US schools, reaching over 45 million children in 180 countries, with a team of just around 200 people [1]. We are now beginning to use this network to give kids the best learning experiences in the world, far beyond those a standard school can provide.
We hire for talent density. Our team comprises the most talented, entrepreneurial, and innovative teammates from around the world, with experience in education and large scale consumer internet companies, including Instagram, Netflix, Dropbox, Stripe, Uber, Y Combinator, and more. We’re building a company where the most talented people want to work. We believe you’ll do the best work of your life here—and you’ll pioneer the future of education, too.
The Role:
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.
What you’ll do:
- 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
What we're looking for:
- Business judgment
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.
- Comfort with messy B2B data
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.
- Analytical problem solving
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.
- Data engineering fluency
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.
- Communication and influence
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.
- Structured, reusable thinking
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 will be a match if:
- You have8+ 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
Bonus:
- 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
[1] Some more context:
(If you are on LinkedIn, you will not be able to access the hyperlinks below. Once you click apply, you will be directed to our career website (if you are not on there already) and will be able to access the hyperlinks)
- How ClassDojo Connects Parents, Students, and Teachers
- “Whats New on ClassDojo 2023”
- TechCrunch Article: Second Act comes with First Profits
Click here if you're interested in learning more about what we've been up to.
We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. In accordance with the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. We are happy to accommodate any disabilities or special needs. We are a distributed company, so we hire regardless of location, as long as you are willing to have significant hours overlap with one of the Americas time zones.
ClassDojo takes a number of factors into consideration when determining compensation, including geographic location, experience, and skillset. Salary ranges (United States):
CA, WA, NY, NJ, CT states: $205,000 - $245,000 (USD)
All other states in the US: $174,500 - $208,500 (USD)
#LI-Remote
Создайте идеальное резюме с помощью ИИ-агента

Навыки
- Python
- GitHub
- Salesforce
- SQL
- dbt
- Statistics
- Airflow
- Data Modeling
- Amazon Redshift
- Metabase
Возможные вопросы на собеседовании
Проверка опыта работы с 'грязными' данными из CRM, что является ключевым требованием вакансии.
Расскажите о случае, когда вам пришлось объединять противоречивые данные из CRM и продуктовых метрик. Как вы обеспечили точность итогового отчета?
Оценка способности кандидата влиять на бизнес-процессы.
Приведите пример, когда ваш анализ напрямую изменил стратегию продаж или маркетинга. Как вы убеждали руководство внедрить эти изменения?
Проверка навыков проектирования архитектуры данных.
Как бы вы спроектировали систему аналитики пайплайна с нуля, чтобы она оставалась масштабируемой и понятной для самостоятельного использования отделом продаж?
Оценка технической автономности (Data Engineering fluency).
Опишите ваш опыт работы с dbt и Airflow. В каких ситуациях вы решите самостоятельно доработать пайплайн, а не ждать помощи инженеров данных?
Проверка умения работать с экспериментами в контексте B2B.
Какие метрики и методы вы бы использовали для оценки эффективности новой стратегии таргетинга в сегменте образовательных округов (districts)?
Похожие вакансии
Middle+ ML разработчик
Senior MLOps Engineer (Platform Development / LLMOps)
Data Scientist Senior (Part-time)
Senior Data инженер
Senior MLOps
Data Engineer / SAP HANA Developer (Senior)
1000+ офферов получено
Устали искать работу? Мы найдём её за вас
Quick Offer улучшит ваше резюме, подберёт лучшие вакансии и откликнется за вас. Результат — в 3 раза больше приглашений на собеседования и никакой рутины!
- Страна
- США
- Зарплата
- 174 500 $ – 245 000 $