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Senior Data Scientist, Growth Alliance (m/f/d)
Отличная позиция в глобальной компании с сильной инженерной культурой. Работа над продуктом с реальным влиянием на миллионы пользователей, современный стек и офис в центре Варшавы делают вакансию крайне привлекательной.
Сложность вакансии
Роль требует не только глубоких знаний в ML и статистике, но и значительного опыта работы с высоконагруженными продакшн-системами, а также умения тесно взаимодействовать с инженерами и продуктовыми командами. Высокая планка ответственности за конверсию и рост бизнеса добавляет сложности.
Анализ зарплаты
Предлагаемая роль Senior Data Scientist в Варшаве соответствует верхнему сегменту рынка для международных продуктовых компаний. Оценки основаны на данных для опытных специалистов в Польше, работающих в крупных технологических хабах.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Data Scientist position within the Growth Alliance at HelloFresh. With over five years of experience in developing and deploying machine learning models, I have a proven track record of building production-ready personalization engines that directly impact business growth and user conversion. My background in regression, classification, and recommendation systems aligns perfectly with your goal of creating an automated engine to determine the optimal user journey.
In my previous roles, I have worked closely with cross-functional teams of engineers and product managers to integrate ML solutions into high-traffic architectures. I am particularly impressed by HelloFresh's commitment to data-driven decision-making and its sophisticated MarTech capabilities. I am confident that my expertise in A/B testing design and my experience in maintaining model performance in production environments will allow me to contribute significantly to the Conversions Tech area and help HelloFresh achieve its ambitious growth targets.
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Откликнитесь в hellofresh уже сейчас
Присоединяйтесь к HelloFresh в Варшаве и создавайте ML-решения, которые персонализируют путь миллионов пользователей к здоровому питанию!
Описание вакансии
Work with HelloFresh in Warsaw and its HelloTech organisation, HelloFresh’s global technology backbone with more than 1000 people, building the digital products that power our end-to-end food experience. From meal kits and ready-to-eat meals to specialty offerings like pet food and premium meat & seafood, HelloTech creates the platforms that bring tailored food solutions to millions of customers every month.
Our subscription-based, direct-to-consumer model relies on technology at every step, from customer-facing apps and personalization logic to pricing, forecasting, supply chain optimization, and initiatives that help reduce food waste. While our brands operate independently to serve distinct customer needs, they are united by shared platforms, data, and operational excellence built by HelloTech.
HelloTech works in autonomous, cross-functional alliances, each owning a specific product or domain end to end. By working with our Warsaw office, you will help shape scalable, data-driven products used across our markets, working with a modern tech stack and international teams to continuously improve how people discover, order, and enjoy HelloFresh’s products, today and in the future.
About the role: What's in the Box
The Conversions Tech area enables meal brands to achieve ambitious growth targets through a seamless and high-performing conversion funnel. As a component of the Growth Alliance, this project drives growth for the HelloFresh group by powering marketing with advanced MarTech capabilities and product innovation. The focus is directed toward (re)acquisition, conversion optimization, and data-driven growth strategies.
In the capacity of a Senior Data Scientist within Conversions, the service provider contributes to shaping the intelligence that drives customized user journeys across conversion funnels. This involves executing complex feature engineering and optimization efforts, contributing to the data foundations and analytical approaches that power the decisioning platform for personalized experiences.
The provided services enable an automated engine that determines the optimal journey for a specific user at the appropriate time, based on intent, channel, and campaign context. This involves operating in a highly cross-functional environment, coordinating closely with Product, Engineering, and Marketing to design, evaluate, and scale personalization across various workstreams. This project carries direct responsibility for advancing the data strategy and improving the user experience for the HelloFresh group across global markets.
What you’ll do: The Recipe
- Build and iterate on machine learning models powering personalization that run in production behind high-traffic, performance-critical conversion pages.
- Execute decisioning models that determine the best next step in the conversion funnel for each user.
- Contribute to system design by coordinating with Engineering to ensure data science solutions integrate cleanly into the overall funnel architecture.
- Coordinate directly with Product and Engineering to shape how ML-driven decisions are embedded into the conversion funnels, including where models decide and how failures are handled.
- Direct experimentation design for decisioning models, defining success metrics, guardrails, and how results are interpreted in high-noise, high-traffic environments.
- Maintain model safety and effectiveness in production by monitoring performance, input data reliability, and latency, and iterating when issues are detected.
What you’ll bring: The Ingredients
- 5+ years of professional experience in data science or a related quantitative field.
- Strong foundation in machine learning concepts relevant to personalization and marketing communications.
- Hands-on experience with techniques such as regression, classification, clustering, recommendation systems, and experimentation.
- Practical experience designing and analyzing A/B tests and controlled experiments.
- Experience working with customer behavior data and segmentation.
- Extensive experience with operating in production environments and collaborating closely with engineers.
- Clear, structured communication skills and a collaborative mindset.
Above all, we are looking for individuals who will make HelloFresh better. We believe there are many different ways of developing skills and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.
What we offer: The Toppings
- Global collaboration at scale: Collaborate with experienced engineers and product partners across HelloTech’s international teams, in a culture of active knowledge sharing.
- Technology with real-world impact: Build and operate modern systems at global scale, supporting 6+ millions of customers and complex supply chain operations.
- Technical/Product/Design leadership: Drive best practices and influence architecture/design, quality, and ways of working in an autonomous, product-led setup.
- End-to-end development/delivery: Drive decisions from problem definition to production, improving systems and enabling long-term scalability.
- Access to workspace at Warsaw Centre Point. The hub offers modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments (coffee, soft drinks, and fruit).
Are you the missing ingredient? If this sounds like a tasty opportunity, we’d be excited to hear from you. We aim to review your profile and respond within 5 business days.
#Data
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Навыки
- Machine Learning
- Python
- A/B Testing
- Regression
- Classification
- Clustering
- Recommendation Systems
- Feature Engineering
- Data Strategy
- System Design
Возможные вопросы на собеседовании
Проверка опыта работы с реальными системами и понимания жизненного цикла модели.
Расскажите о самом сложном случае внедрения ML-модели в продакшн: с какими техническими ограничениями вы столкнулись и как их решили?
Важно для роли в Growth Alliance, где шумные данные — норма.
Как вы подходите к дизайну A/B тестов в условиях высокого уровня шума и как определяете необходимые метрики-guardrails?
Оценка навыков в области персонализации и маркетинговых технологий.
Какие методы вы бы использовали для определения 'лучшего следующего шага' пользователя в воронке конверсии при холодном старте (отсутствии истории)?
Проверка умения работать в кросс-функциональной среде.
Как вы выстраиваете коммуникацию с инженерами, чтобы ваши модели легко интегрировались в общую архитектуру продукта?
Оценка навыков мониторинга и поддержки систем.
Как вы организуете мониторинг дрейфа данных (data drift) и падения точности моделей для системы, работающей в реальном времени?
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