- Страна
- США
- Зарплата
- 168 100 $ – 186 600 $
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Senior Applied Scientist, Demand Forecasting
Отличная позиция в стабильной международной компании с прозрачным диапазоном зарплаты и сильным социальным пакетом. Работа напрямую влияет на экологическую повестку (сокращение отходов) и операционную эффективность бизнеса.
Сложность вакансии
Роль требует глубоких знаний в области машинного обучения и оптимизации, а также опыта работы с крупными цепочками поставок. Высокий уровень ответственности за бизнес-критичные решения и необходимость менторства повышают планку требований.
Анализ зарплаты
Предложенный диапазон $168k–$186k полностью соответствует рыночным стандартам для позиции Senior Applied Scientist в Нью-Йорке, где медиана составляет около $180k. Верхняя граница предложения конкурентоспособна для сектора e-commerce и логистики.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Applied Scientist position at HelloFresh. With over three years of experience in applying machine learning and statistical modeling to complex operational challenges, I am particularly drawn to the opportunity to optimize demand forecasting within your sophisticated US supply chain. My background in developing scalable data pipelines and mathematical optimization models aligns perfectly with your team's mission to reduce waste and enhance efficiency.
In my previous roles, I have successfully translated complex scientific insights into actionable business tools, working closely with cross-functional teams in procurement and logistics. I am proficient in Python, SQL, and cloud ecosystems like Databricks and AWS, and I thrive in fast-paced environments where scientific rigor meets business pragmatism. I am excited about the prospect of mentoring junior team members and contributing to the technical excellence of the Demand Forecasting team at HelloFresh.
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Описание вакансии
As an Applied Scientist on the Demand Forecasting team, you will help shape how HelloFresh predicts and plans customer demand across our US supply chain. Your work will sit at the intersection of data science, optimization, and operations. You’ll be building models that directly drive business-critical decisions from menu planning and procurement to fulfillment.
You’ll partner closely with product, engineering, and operations teams to design, test, and deploy advanced forecasting and decision systems. You’ll explore and apply state-of-the-art machine learning and statistical techniques to improve forecast accuracy, quantify uncertainty, and enable better planning decisions. Beyond building models, you’ll play a key role in translating complex scientific insights into scalable tools and strategies that enhance efficiency and reduce waste throughout the supply chain.
You will…
- Develop, prototype, and deploy forecasting models that capture complex demand patterns and constraints across multiple brands, products, and time horizons.
- Build scalable data pipelines leveraging Databricks, Snowflake, and AWS.
- Create mathematical optimization models and tools to solve practical business problems; roll them out.
- Collaborate cross-functionally with procurement, planning, and operations teams to translate scientific work into measurable business outcomes.
- Identify problems proactively, formulate and implement robust and data-driven solutions.
- Mentor and support analysts, engineers, and scientists within the team. Share best practices in modeling, and scientific rigor to elevate overall team technical excellence.
You are...
- A hands-on problem solver with experience applying scientific methods to real-world operational challenges.
- Skilled in Python and familiar with common machine learning and optimization techniques.
- Experienced in data manipulation and analytics within cloud-based ecosystems.
- Agile – you thrive in fast-paced and dynamic environments and are comfortable working autonomously
- Comfortable balancing scientific rigor with business pragmatism; able to communicate insights effectively to both technical and non-technical audiences.
- Detail-oriented – you possess strong organizational skills and consistently demonstrate a methodical approach to all your work.
You have…
- A degree in a quantitative field such as Computer Science, Statistics, Applied Mathematics, Operations Research, or a related discipline (Master’s or PhD preferred).
- 3+ years of experience applying machine learning, forecasting, or statistical modeling in an applied business setting.
- 2+ years of experience building tools/applications in a high-level language, such as Python or Java.
- Experience working with large, complex datasets using SQL and Python-based data ecosystems.
- Familiarity with operations and supply chain management concepts - forecasting, planning, optimization, logistics experience preferred.
You’ll get…
- Competitive hourly rate, 401K company match that vests immediately upon participation, & team bonus opportunities
- Generous PTO and flexible attendance policy
- Comprehensive health and wellness benefits with options at $0 monthly, effective first day of employment
- Up to 85% discount on subscriptions to HelloFresh meal plans (HelloFresh, Green Chef, Everyplate, and Factor_)
- Access to Employee Resource Groups that are open to all employees, including those pertaining to BIPOC, women, veterans, parents, and LGBTQ+
- Inclusive, collaborative, and dynamic work environment within a fast-paced, mission-driven company that is disrupting the traditional food supply chain
This job description is intended to provide a general overview of the responsibilities. However, the Company reserves the right to adjust, modify, or reassign work tasks and responsibilities as needed to meet changing business needs, operational requirements, or other factors.
New York Pay Range
$168,100—$186,600 USD
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Навыки
- Python
- Machine Learning
- SQL
- Databricks
- Snowflake
- AWS
- Mathematical Optimization
- Statistics
- Supply Chain Management
- Data Pipelines
Возможные вопросы на собеседовании
Проверка опыта работы с временными рядами и спецификой спроса.
Как вы подходите к моделированию сезонности и праздничных аномалий в прогнозировании спроса на продукты питания?
Оценка навыков работы с неопределенностью, что критично для планирования запасов.
Какие методы вы используете для количественной оценки неопределенности прогноза и как вы объясняете эти интервалы бизнес-заказчикам?
Проверка технических навыков работы с большими данными.
Опишите ваш опыт построения масштабируемых пайплайнов данных с использованием Databricks или Snowflake для задач ML.
Оценка умения находить баланс между точностью и применимостью.
Расскажите о случае, когда вам пришлось пожертвовать сложностью модели ради её интерпретируемости или скорости работы в продакшене.
Проверка знаний в области исследования операций.
Как вы интегрируете результаты прогнозных моделей в математические модели оптимизации для цепочки поставок?
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- Страна
- США
- Зарплата
- 168 100 $ – 186 600 $