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Freelance Data Scientist - AI Marketplace Platform

Оценка ИИ

Отличная позиция в компании-единороге с сильной инженерной культурой и современным стеком. Масштаб задач (450+ маркетплейсов) гарантирует профессиональный рост, хотя гибридный график ограничен одним днем удаленки.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует серьезного опыта (от 3 лет) в прикладном ML и умения выводить модели в продакшн. Процесс отбора включает технический кейс и несколько этапов интервью, что подтверждает высокие стандарты компании.

Анализ зарплаты

Медиана65 000 €
Рынок55 000 € – 80 000 €
Оценка ИИ

Указанная роль соответствует уровню Middle/Senior Data Scientist во Франции. Рыночные зарплаты в Бордо и Париже для специалистов с опытом от 3 лет обычно находятся в диапазоне 55,000–75,000 евро в год, что делает позицию конкурентоспособной.

Сопроводительное письмо

I am writing to express my strong interest in the Data Scientist position at Mirakl. With over three years of experience in applied machine learning and a deep proficiency in Python, PyTorch, and TensorFlow, I have a proven track record of moving algorithms from prototype to production. My background in developing anomaly detection systems and working with Transformer architectures aligns perfectly with your current initiatives, such as price monitoring and sentiment analysis.

What excites me most about Mirakl is the opportunity to work within a large-scale data ecosystem that impacts over 450 global marketplaces. I am particularly drawn to your focus on agentic commerce and the development of AI agents to empower sellers. I am a pragmatic, data-driven professional who thrives in collaborative environments, and I am eager to contribute to the continued success of your 60+ person Data team while leveraging tools like Databricks, Spark, and AWS.

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Присоединяйтесь к команде Mirakl и создавайте AI-решения, которые изменят облик мировой электронной коммерции!

Описание вакансии

About Mirakl:

Founded in 2012, Mirakl has been at the forefront of marketplace innovation, empowering every business to compete in the platform economy.

Today, Mirakl’s operating system combines an enterprise marketplace solution (Mirakl Platform) that enables retailers and B2B organizations to launch, scale, and operate marketplaces and dropship, AI-powered multichannel selling (Mirakl Connect), retail media (Mirakl Ads) and an agentic commerce infrastructure (Mirakl Nexus).

With dual headquarters in Boston and Paris, Mirakl helps a global ecosystem of 450+ marketplaces (B2C and B2B) and a network of over 100k third-party marketplace sellers. Brands like Macy’s, Decathlon, Carrefour, Asos, and Airbus Helicopters use Mirakl to grow their businesses in new and remarkable ways.

For more information: www.mirakl.com.

Mirakl in Numbers:

  • 🗓️ Founded in 2012 | Member of French Tech Next40
  • 👥 750+ employees in 9 offices worldwide: Paris, Barcelona, Bordeaux, Boston, London, Munich, New York, Sydney, Tokyo
  • 🇫🇷 350+ Mirakl Tech teams members mainly based in France
  • ⚙️ 5 Saas Solutions

Our Values:

Working at Mirakl means accelerating your career alongside ambitious, passionate, and supportive colleagues. We're proud of the diversity of backgrounds, perspectives, and experiences that make our teams unique.

Our 5 values guide how we collaborate:

  • 💡 Work Hard Together: Teamwork and collaboration are the foundation of our success
  • 🏆 Get Things Done:  We prioritize action and efficiency for impactful results
  • 🚀 Go Above & Beyond:  We tackle challenges proactively and always aim for excellence
  • 🎓 Succeed Through Expertise: Knowledge sharing and continuous learning are core to our culture
  • 🤝 Satisfy & Empower Clients: We're committed to our clients' success

About the job

As part of our Data team (60+ people), your main mission will be to prototype, iterate, and put algorithms into production in collaboration with the Product teams, Data Engineers, and Development teams.

The topics you will be working on will have a real impact on 450+ of the world's largest retailers (Best Buy, Decathlon, Leroy Merlin, Macy's, etc.) and 100k+ sellers. The goal is to make the most of our rich and varied data in order to increase their revenue, optimize the operational management of their businesses, and ensure the security of users and transactions.

We are looking for someone on a permanent contract, based in Paris or Bordeaux (1 day remote per week).

Here are some of the current and future topics the team is working on:

  • Detecting anomalies in product prices
  • Analyzing sentiment in seller/consumer exchanges to prioritize critical messages
  • Estimating package delivery times
  • Predicting and anticipating stock shortages
  • Detecting anomalies in seller behavior
  • Developing AI agents to help sellers take action on their businesses

This job offers you:

  • Implementing algorithms that will have a visible impact on more than 500 e-commerce sites/marketplaces in 40 countries, some of which are very large (millions of products, customers, orders per year)
  • A wide variety of techniques (time series, heuristics, deep learning, NLP, LLM, etc.).
  • Real autonomy and responsibility in the projects you own

Our stack and tools:

Python, Tensorflow, Keras, Pytorch, Databricks, Spark, AWS (Amazon Redshift, s3, etc.), SQL, Airflow, Delta Lake

On a daily basis, you will:

  • Analyze and prepare data, prototype algorithms
  • Put them into production in collaboration with Data Engineers and development teams
  • Create dashboards to illustrate the relevance of algorithms and monitor production
  • Present results at weekly data science meetings and participate in team brainstorming sessions
  • Liaise with other teams to refine use cases, user experience, and integration methods

You will enjoy this job if:

  • You have a background in machine learning, mathematics, computer science (or a related field)
  • You already have 3 years of experience in a similar position
  • You have significant experience in applied ML in a business setting
  • You have a good knowledge of machine learning and deep learning algorithms (particularly state-of-the-art architectures, such as Transformers)
  • You are proficient in Python, Tensorflow, and/or PyTorch.
  • You are pragmatic, data-driven, and business-oriented with good team spirit.
  • You like to take ownership of your projects and are curious.
  • You have a positive attitude: respect and kindness are part of your values.

Want to join us? ⭐

  • A 30-minute phone call with one of our Tech recruiters. This will be an opportunity to discuss your background and expectations, and to find out what Mirakl can offer you in return.
  • An initial 30-minute technical discussion via Zoom with a member of the Data Science team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
  • A practical case study to complete at home.
  • A 75-minute technical review and discussion with a manager from the Data Science team.
  • A final 1-hour Zoom meeting with future Mirakl colleagues to discuss our values and corporate culture.

We welcome collaborators with their diverse perspectives and experiences to power us forward. These often far exceed conventional job requirements and help us create a culture of continuous learning. If you’re ready to join a global leader powering digital transformation for 450+ of the world’s most innovative retailers and B2B organizations..

We may use Artificial Intelligence (AI) solutions to help streamline our hiring process, including screening applications, analyzing resumes, and assessing responses. While AI helps us work efficiently, all final hiring decisions are made by humans. For more information, visit our AI Guidelines for Candidates and Interviews.

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Навыки

  • Python
  • TensorFlow
  • Keras
  • PyTorch
  • Databricks
  • Spark
  • AWS
  • Amazon Redshift
  • SQL
  • Airflow
  • Delta Lake
  • NLP
  • Deep Learning
  • Machine Learning
  • Transformers

Возможные вопросы на собеседовании

Вакансия упоминает работу с временными рядами для прогнозирования доставки и дефицита товаров.

Как вы подходите к обработке пропущенных данных и аномалий в высокочастотных временных рядах при прогнозировании сроков доставки?

Компания активно внедряет современные архитектуры для анализа текстов.

Опишите ваш опыт тонкой настройки (fine-tuning) трансформеров для задач анализа тональности в специфическом домене e-commerce.

Работа предполагает тесное сотрудничество с Data-инженерами для деплоя моделей.

Расскажите о самом сложном случае вывода ML-модели в продакшн: с какими проблемами производительности или масштабируемости вы столкнулись?

Одной из задач является обнаружение аномального поведения продавцов.

Какие методы обучения без учителя (unsupervised learning) вы бы использовали для обнаружения мошенничества на маркетплейсе при отсутствии размеченных данных?

Mirakl использует стек Databricks и Spark.

Каков ваш опыт работы с распределенной обработкой данных в Spark для подготовки признаков (feature engineering) на терабайтных выборках?

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