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Data Scientist (m/f/x)
Отличная вакансия с прозрачными бонусами: опционы, бюджет на обучение 3600€ и поддержка релокации. Компания работает в интересном домене (IoT/Railway) и предлагает современный стек технологий.
Сложность вакансии
Роль требует уверенных навыков программирования на Python и опыта работы с IIoT данными. Хотя это не позиция Senior, ожидается умение доводить модели до продакшена и работать в междисциплинарной команде.
Анализ зарплаты
Зарплата в объявлении не указана, но для Data Scientist с опытом 2+ года в Мюнхене рыночный диапазон составляет 65,000–85,000 евро. Предложение KONUX включает опционы (equity), что может значительно увеличить совокупный доход в долгосрочной перспективе.
Сопроводительное письмо
I am writing to express my strong interest in the Data Scientist position at KONUX. With over two years of experience in building and deploying machine learning models, I am particularly drawn to your mission of transforming the railway industry through AI-powered IIoT solutions. My background in handling complex sensor data and my proficiency in Python, pandas, and SQL align perfectly with the technical requirements of your team.
In my previous roles, I have focused on delivering end-to-end solutions, from initial data exploration to production-grade deployment. I am impressed by KONUX's commitment to a culture of grit and ingenuity, and I am eager to bring my proactive, impact-driven attitude to your engineering department. I am especially excited about the opportunity to work with diverse datasets, including time-series and sensor data, to drive real-world impact in the IoT space.
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Описание вакансии
About Us:
KONUX is a dynamic and fast-growing technology company that is transforming the railway industry. Our AI-powered solutions empower our customers to make smarter, data-driven decisions. Our culture is fueled by grit, ingenuity, and credibility. We believe these values are essential to unlocking technology's potential and making a real impact. At KONUX, we are passionate about driving innovation in the fields of IoT and AI, and we are looking for like-minded individuals to join our team.
Job Description:
We are seeking a Data Scientist (f/m/x) to join our team of innovators. In this role, you will be at the forefront of developing groundbreaking solutions that solve real-world problems. You will work alongside a team of experts who are committed to pushing the boundaries of what's possible and driving innovation forward. If you're a go-getter who's not afraid to think outside the box, we want to hear from you. You'll be a key driver of our culture, helping to ensure that our values are embedded in everything we do.
Your Impact:
- Develop insights using a wide range of data sources, including IIoT sensor data and other railway domain datasets
- Design and implement solutions - from understanding customer challenges to releasing models to production
- Deploy well-tested, maintainable solutions into live systems
- Develop tools and infrastructure for sensor data analysis that integrate smoothly into our end-to-end software engineering lifecycle
- Collaborate closely with engineers, product managers, and domain experts to translate business needs into technical impact
To be successful in this role, you’ll need to have:
- A degree in Mathematics, Statistics, Computer Science, Engineering, or a related field with 2+ years of hands-on experience in data science, having built and tested statistical or ML models
- Solid programming skills in Python and past experience working with dataframe-centric data manipulation tools such as pandas, PySpark, Polars and SQL
- Motivation to learn about production-grade systems and software engineering practices, delivering solutions end-to-end
- A collaborative mindset and an eagerness to learn and grow
- A proactive, impact-driven attitude and the ability to thrive in a fast-paced, collaborative environment
It’s a plus if you have:
- Proficiency in additional programming languages and understanding of software engineering best-practices, testing, version control (Git), and CI/CD workflows
- Worked with and trained models using diverse types of data (e.g. time-series, tabular, event logs, images, sensor data etc.)
- Experience with state-space and survival modeling, and familiarity with statistical packages such as statsmodels, PyMC, or Stan
If you’re excited about this role but your experience doesn’t align perfectly with every qualification, we still encourage you to apply. At KONUX, we know that great talent comes in many forms, and your unique background could be an excellent fit for our team.
Why Join Us:
💸 Competitive salary
📉 Equity (all permanent KONUX employees have equity!)
📖 Dedicated Learning & Development budget of 3.600€ p.a.
🏠 Comprehensive relocation support if this opportunity at KONUX requires you to move
👨💻 Hybrid working model: Meet your colleagues in the office minimum 2 days per week
🏢 Modern workspace with a cool rooftop with a mountain view
💻 Flexible working conditions, home office equipment and free choice between a Windows or Apple laptop
❤️🩹 Health benefits supporting your physical and mental well-being, e.g wellpass/gym membership and mental health app license
🍒Fruits, snacks and beverages for energy and our very own Oma cooking in the office every Thursday
👴 Company pension scheme
🙌 Access to Corporate Benefits and Future Bens
🌴 27 vacation days (+1 day on every work anniversary for 3 years)
💁 Volunteering activities (2 additional days off)
🍻 Company and team events
🐶 We are a pet-friendly company, so your four-legged friend can join you in the office!
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Навыки
- Git
- Python
- Pandas
- Machine Learning
- SQL
- Statistics
- CI/CD
- PySpark
- IoT
- Polars
- Stan
- statsmodels
- Time Series Analysis
- PyMC
Возможные вопросы на собеседовании
Вакансия предполагает работу с данными датчиков IIoT, что часто требует специфических навыков обработки временных рядов.
Расскажите о вашем опыте работы с данными временных рядов или датчиков: с какими основными проблемами (шум, пропуски) вы сталкивались?
Компания ищет кандидата, способного внедрять решения в реальные системы.
Как вы подходите к тестированию и деплою ML-моделей в продакшн-среду?
В описании упоминаются PySpark и Polars как инструменты для работы с данными.
В каких ситуациях вы бы предпочли использовать Polars или PySpark вместо стандартного pandas?
Упоминание survival modeling в секции 'плюсов' указывает на специфические задачи прогнозирования отказов.
Знакомы ли вы с анализом выживаемости (survival analysis) и как его можно применить для прогнозирования состояния оборудования?
Работа в KONUX предполагает тесное взаимодействие с инженерами и менеджерами продуктов.
Опишите случай, когда вам пришлось переводить сложную техническую проблему на язык бизнеса для продуктовой команды.
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