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asana
Страна
США
Зарплата
202 000 $ – 282 000 $
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Staff Data Scientist, Marketing

Оценка ИИ

Престижная компания с отличной культурой, прозрачная вилка зарплаты выше рынка и возможность влиять на стратегию крупного продукта. Гибридный формат работы в Сан-Франциско добавляет привлекательности для местных кандидатов.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль уровня Staff требует не только глубоких технических знаний в области причинно-следственного вывода и MMM, но и развитых лидерских качеств для менторства и формирования технической стратегии всей команды. Высокая планка ожиданий по опыту работы с маркетинговыми моделями в продакшене.

Анализ зарплаты

Медиана235 000 $
Рынок195 000 $ – 290 000 $
Оценка ИИ

Предлагаемая зарплата ($202k - $282k) полностью соответствует и даже несколько превышает медианные значения для позиций уровня Staff Data Scientist в Сан-Франциско, которые обычно варьируются от $210k до $250k. Дополнительные компоненты в виде акций (equity) делают предложение крайне конкурентоспособным.

Сопроводительное письмо

I am writing to express my strong interest in the Staff Data Scientist, Marketing position at Asana. With over six years of experience in data science and a proven track record of leading technical roadmaps for marketing effectiveness, I am confident in my ability to serve as a Solution Architect for your core projects. My expertise in Media Mix Modeling (MMM), User Lifetime Value (LTV), and causal inference aligns perfectly with Asana's mission to foster a data-driven approach in shaping business strategies.

Throughout my career, I have specialized in designing and deploying scalable production ML solutions, particularly within the marketing domain. I have extensive experience collaborating with marketing leadership to integrate data science into business operations and a passion for mentoring team members to elevate their technical rigor. My proficiency in SQL, Python, and MLOps tools like MLFlow, combined with my background in advanced statistical modeling, positions me to contribute immediately to Asana’s high-performing data community.

I am particularly drawn to Asana’s commitment to a data-driven culture and its recognition as a top workplace. I look forward to the possibility of bringing my technical leadership and hands-on expertise to your San Francisco team to drive impactful results and enhance Asana’s marketing effectiveness.

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Составьте идеальное письмо к вакансии с ИИ-агентом

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Откликнитесь в asana уже сейчас

Присоединяйтесь к Asana, чтобы определять будущее маркетинговых стратегий с помощью передовых технологий анализа данных и машинного обучения!

Описание вакансии

The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana’s marketing effectiveness. You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities. You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design.

This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve:

  • Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
  • Act as the primary technical subject matter expert for the Marketing Data Science team, setting the technical bar for modeling quality, code rigor, data pipeline architecture, and solution scalability.
  • Collaborate with marketing leadership to pinpoint how data science can be further integrated into Asana's business approach.
  • Provide hands-on technical mentorship and guidance to a team of data scientists at varying levels, helping them navigate complex modeling challenges, choose appropriate methodologies, and establish robust ML Ops.
  • Develop and standardize MLOps tooling and processes that enable the team to deploy, monitor, and maintain multiple models in production efficiently and reliably.
  • Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation.
  • Take on a technical leadership role within the broader Asana Data Community, interacting with Data Engineering and Platform teams to influence the data and MLOps infrastructure required to support marketing data products.

About you:

  • Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience
  • 6+ years of experience in a data science role, with 2+ years dedicated to technical leadership and mentorship of other data scientists, successfully driving the architecture and execution of large-scale production data science projects
  • 4+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
  • Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
  • Proven track record developing, deploying, and maintaining scalable production ML solutions and data products
  • Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus
  • Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.

What we’ll offer:

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between $202,000 - $282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

  • Mental health, wellness & fitness benefits
  • Career coaching & support
  • Inclusive family building benefits
  • Long-term savings or retirement plans
  • In-office culinary options to cater to your dietary preferences

These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

#LI-Hybrid #LI-AA1

About us

Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong.

Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

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Навыки

  • Python
  • Machine Learning
  • SQL
  • Statistics
  • MLOps
  • Spark
  • MLflow
  • R
  • Redshift
  • Causal Inference
  • Media Mix Modeling
  • Lifetime Value

Возможные вопросы на собеседовании

Проверка глубоких знаний в ключевой области маркетинговой аналитики, указанной в вакансии.

Расскажите о вашем опыте построения моделей Media Mix Modeling (MMM). С какими основными проблемами вы сталкивались при оценке инкрементальности каналов?

Оценка навыков архитектурного планирования и понимания жизненного цикла ML-моделей.

Как бы вы спроектировали масштабируемую систему для расчета User Lifetime Value (LTV) в реальном времени для SaaS-продукта?

Важная часть роли Staff — это наставничество и повышение стандартов кода.

Опишите ваш подход к внедрению практик MLOps в команде. Как вы обеспечиваете воспроизводимость и надежность моделей в продакшене?

Проверка способности обосновывать технические решения перед бизнесом.

Как вы объясняете маркетинговому руководству разницу между корреляцией и причинно-следственной связью при анализе эффективности рекламных кампаний?

Оценка лидерских качеств и умения разрешать технические конфликты.

Приведите пример, когда вам пришлось принимать сложное архитектурное решение, с которым не все были согласны. Как вы аргументировали свою позицию?

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asana
Страна
США
Зарплата
202 000 $ – 282 000 $