Descrição da vaga

Texto agregado para leitura rápida. Confira sempre a fonte original ao enviar a candidatura.

Ambush is a people first company where talented, thoughtful individuals come together to build meaningful products and lasting partnerships. We believe the best work happens when people feel supported, trusted and empowered to bring their full abilities to the table.

Since 2015, because of our people first and long term mindset, we have grown into a partner relied on by some of the best companies in the world. We combine strong engineering, design and strategy with a growing strength in AI to help our clients see what is next and achieve bigger outcomes.

At the heart of everything we do is our team. We collaborate, take risks, lift each other up and take pride in doing work the right way, not settling for a quick makeshift solution. If you join Ambush, you join a group of people who want you to succeed and who show up for each other every day.

We believe in and expect real teamwork, a constant drive to be better, and delivering meaningful long term outcomes that we can be proud of together.

What we'd like to see in a candidate:

Strong programming skills in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and SQL.

Proven experience in Data Science, Data Analysis, or related roles.

Solid foundation in statistics, data modeling, and applied machine learning.

Hands-on experience with cloud platforms (AWS preferred: SageMaker, Lambda, RDS, S3).

Ability to communicate insights clearly to both technical and non-technical stakeholders.

Experience with version control (Git) and modern development practices.

Excellent English communication.

Nice to haves:

Background in scientific research or advanced studies (MSc/PhD in a quantitative field).

Experience with LLMs (e.g. GPT, LangChain, Whisper, vector databases) or graph neural networks.

Proficiency with full-stack or API development (FastAPI, Next.js, etc.) to deliver data products.

Familiarity with big data tools (Spark, BigQuery, Redshift).

Exposure to fraud detection, anomaly detection, or other high-impact ML use cases.

Knowledge of efficient compiled languages (C++, Rust, Scala) for numerical computation.

Knowledge of GNSS.

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