yandex
hellofresh
Страна
Канада
Зарплата
90 000 CA$ – 100 000 CA$
+500% приглашений

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ГибридКонтракт

Data Scientist

Оценка ИИ

Сильный бренд, прозрачный диапазон зарплаты и отличный пакет льгот (включая скидки на еду и поддержку здоровья). Гибридный формат работы и фокус на развитии сотрудников делают вакансию очень привлекательной.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует уверенных знаний в статистике и опыта работы с ML-моделями (2-3 года). Основная сложность заключается в необходимости интеграции в глобальную ML Ops платформу и умении объяснять сложные концепции нетехническим стейкхолдерам.

Анализ зарплаты

Медиана105 000 CA$
Рынок85 000 CA$ – 130 000 CA$
Оценка ИИ

Предложенная зарплата в 90,000 – 100,000 CAD соответствует рыночному уровню для специалистов среднего звена (Intermediate) в Торонто, хотя верхняя граница рынка для опытных Data Scientist может быть выше.

Сопроводительное письмо

I am writing to express my interest in the Data Scientist position at HelloFresh. With over 2 years of experience in building and deploying machine learning models, I am particularly drawn to this role's focus on driving business value through deep analytical dives and scalable data products. My background in Python, SQL, and advanced statistics aligns perfectly with your team's requirements for developing effective data science solutions.

In my previous roles, I have successfully collaborated with cross-functional teams to deliver data-driven insights and maintain ML pipelines. I am excited about the opportunity to contribute to HelloFresh's global ML Ops platform and leverage my expertise in A/B testing and time-series analysis to optimize operations and customer experience. I am especially impressed by your commitment to a flexible hybrid work culture and your focus on continuous learning and development.

+250% к просмотрам

Составьте идеальное письмо к вакансии с ИИ-агентом

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Откликнитесь в hellofresh уже сейчас

Присоединяйтесь к HelloFresh и создавайте инновационные ML-решения для мирового лидера в доставке продуктовых наборов!

Описание вакансии

\*\*This position is an 18 Month Contract\*\*

S'more about the team

The Data Scientist is responsible for building, testing, and deploying statistical and machine learning models, and conducting deep analytical data dives to drive better understanding of our customers, products, and operations. Reporting to the Manager of Data Operations, this role will be responsible for designing and developing effective and scalable data science solutions to solve complex problems across our business and advance our data capabilities.

Lettuce share what this role will be responsible for

  • Collaborate with data engineers, business intelligence analysts, automation specialists, and other stakeholders to deliver best in class data science and machine learning solutions
  • Lead the design, build and deployment of data products, including statistical and machine learning models, data deep dives and statistical testing / analyses, to a wide range of stakeholder groups across various applications.  Some examples include:
  • Develop project plans based on large-scale stakeholder requirements, and provide updates to data team peers and stakeholders on the delivery of these
  • Maintain up-to-date knowledge and understanding of machine learning and deep learning algorithms, AI tools, etc., and their potential applications to the business, making recommendations for evaluation/testing where relevant
  • Liaise with Global data science teams to identify opportunities for collaboration, support, code reviews, and adoption of new tools / techniques
  • Contribute to the development and implementation of the global ML Ops platform in Canada
  • All other duties, as assigned

Sound a-peeling? Here's what we're looking for

  • 2-3 years experience in data science, data engineering and/or other relevant data disciplines
  • Experience identifying business opportunities for data science and ML solutions, scoping and prioritizing projects, and resourcing with appropriate skills
  • Good grasp of advanced statistical concepts (e.g., Bayesian statistics; multilevel and generalized linear models; timeseries; bootstrapping) as well as various data science methodologies (e.g., NLP/LLM, quasi experimentation, A/B testing, etc.)
  • Intermediate Python programming
  • Advanced SQL Querying
  • Understanding of data visualization best practices and proficiency with BI Platforms (Tableau preferred)
  • Strong, demonstrable analytical and problem-solving skills
  • Ability to communicate complex concepts and analyses to both technical and non-technical stakeholders
  • Bachelor’s degree in STEM, Economics or Business preferred, or equivalent work experience

Let’s cut to the cheese, this is why you'll love it here

  • *Box Discount* - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
  • *Health & Wellness* -Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
  • *Vacation & PTO* -Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance.
  • *Family Benefits* - A parental leave top-up program for expectant parents.
  • *Growth & Development* - We support your career progression, provide development opportunities, and invest in your continued learning through our organization wide L&D fund.
  • *Work Hard & Have Fun* - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
  • *Diversity & Inclusion Initiatives* - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
  • *Food Puns* - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!

Flexible Hybrid Approach

At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. 

To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.

#LI-HYBRID

Working Conditions

It’s no surprise that as a food company, we use many ingredients that may be considered common allergens (i.e. peanuts, tree nuts, milk, etc.). Whether this role is based out of our headquarters or one of our distribution centers, it is possible that you may be exposed to such allergens in this role. If you have any concerns with being exposed to any particular food ingredients, including meat, please disclose this during the hiring process.

HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.

This is a posting for an existing vacancy. We are actively seeking to fill this position.

*Interested in joining the HelloFresh team? Don’t be chai, apply! Submit your application in PDF format today.*

Toronto, ON Pay Range

$90,000—$100,000 CAD

+400% к собеседованиям

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Навыки

  • Python
  • SQL
  • Tableau
  • Machine Learning
  • Statistics
  • NLP
  • LLM
  • A/B Testing
  • Time Series
  • MLOps
  • Data Visualization

Возможные вопросы на собеседовании

Проверка понимания основ статистики, указанных в требованиях (Bayesian, GLM).

Можете ли вы объяснить разницу между байесовским и частотным подходами к статистическому выводу на примере бизнес-задачи?

Вакансия упоминает участие в разработке ML Ops платформы.

Расскажите о вашем опыте развертывания моделей в продакшн и какие инструменты ML Ops вы использовали для мониторинга их производительности?

В описании указаны NLP и LLM как желаемые методологии.

Был ли у вас опыт работы с большими языковыми моделями (LLM) для решения бизнес-задач, например, для анализа отзывов клиентов?

Работа предполагает тесное взаимодействие с инженерами данных и аналитиками.

Опишите случай, когда вам пришлось переводить сложные технические результаты вашего анализа на язык, понятный бизнес-руководству.

HelloFresh активно использует A/B тестирование.

Как бы вы подошли к дизайну эксперимента для оценки влияния новой функции в приложении на удержание пользователей (retention)?

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hellofresh
Страна
Канада
Зарплата
90 000 CA$ – 100 000 CA$