I applied online. The process took 2 weeks. I interviewed at Stenon (Cuiabá, Mato Grosso) in Oct 2025
Interview
Entrevista com 2 etapas, conduzida em inglês com o time da Stenon, procesos muito bem desenvolvidos e claro em todas etapas. Fiquei Feliz ao realizar a entrevista e passar em todas as etapas.
- Short Call with CFO - Get to know me
- Case Study Interview with CTO and CFO - preparation of case study in advance - presentation of results and answering of questions in interview
- Offer via Mail
Interview questions [1]
Question 1
Are you okay that not everyday will be the same at work?
I applied online. The process took 2 weeks. I interviewed at Stenon (Berlin) in Dec 2024
Interview
The interview process was structured, transparent, and engaging. It consisted of:
1. An initial call with the CTO to discuss my background and the company’s vision.
2. A second call with the CTO focusing on technical and problem-solving questions to evaluate my approach to challenges.
3. A home task followed by a presentation to the team, showcasing my proposed solution and answering their questions.
4. A follow-up session with a Data Engineer to understand the tasks I’d be handling.
5. A final conversation with the CEO to discuss overall fit and company culture.
6. A fast decision after the weekend, including a call with the CTO to address open topics like salary, vacations, and equipment.
The process gave me a great opportunity to meet the team, gain insights into the work culture, and understand the challenges I’d be tackling. I appreciated the focus on my thought process, the "why and how" of problem-solving, and tool selection.
Overall, I had a very positive experience and felt the team was genuinely interested in finding the right fit both professionally and personally.
Interview questions [1]
Question 1
- Erzählen Sie etwas über Ihren beruflichen Hintergrund.
- Wie würden Sie Datenpipelines für IoT-Geräte entwerfen und implementieren?
- Welche Schritte unternehmen Sie, um die Arbeit eines Data-Science-Teams effizient zu organisieren (z. B. Model Registry, Training, Deployment)?
- Wie gehen Sie an komplexe Probleme heran und wählen die passenden Tools aus?
- Können Sie ein Beispiel geben, bei dem Sie ein bestehendes Problem mit einer kreativen Lösung adressiert haben?
- Wie stellen Sie die Datenqualität in einer Data-Pipeline sicher?
- Haben Sie Erfahrung mit bestimmten Technologien wie MLFlow, Airflow, oder AWS?