Ambush is a People Company. But what does that mean exactly? It means we care about our people as much as we care about building great products. We take a human-centered approach to identifying, retaining and integrating highly-talented, long-term remote people into America’s best product and development team. We began our consulting journey in 2015 and have been growing ever since! We do that by delivering the best quality work possible for our clients. We are not afraid to take risks and we always seek the best possible path to solve a problem, instead of just a quick makeshift solution. Thanks to our highly skilled team of engineers, we always perform tasks using our best abilities! We are passionate about what we do everyday and we can always count on our team to have our backs. Teamwork is one of our core values! We don’t go anywhere by ourselves. We are driven to achieve great things. And we are extremely helpful to everyone. We expect you to be a team player. When you join us, you will:Build, validate, and deploy statistical and machine learning models (e.g. anomaly detection, fraud detection, clustering, NLP, generative AI). Experiment with advanced techniques (e.g. graph neural networks, LLMs, deep learning) to push the boundaries of what data can deliver. Collaborate with engineering, product, and business teams to translate strategic questions into data-driven solutions. Contribute to architectural discussions on scalable, production-ready ML systems. Share your knowledge with a team of passionate engineers and help foster a culture of agile, data-driven decision-making. Use your excellent English skills to communicate daily, both verbally and in writing, in cross-functional teams. 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.