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Senior Data Scientist

1 week ago

Copenhagen, Copenhagen, Denmark Alipes ApS Full time

Imagine working with cutting-edge machine learning models and designing robust software infrastructure that supports seamless training, deployment, and monitoring of predictive models. At Alipes Capital, we're building a world-class ML engineering workflow to transform massive unstructured financial data sets into production-ready inference models that drive real-time trading decisions.

You'll have the opportunity to develop scalable high-performance ML systems, ensuring a smooth pipeline from dataset generation through model prototyping to production deployment.

  • Designing infrastructure to support distributed model training and experiment tracking.
  • Building automated data pipelines for dataset generation and feature engineering, while enabling data version control.
  • Developing software for rapid experimentation and deployment, including automated testing and continuous integration.
  • Implementing best practices in software development, ensuring maintainability, scalability, and efficiency of ML systems through automated testing and real-time monitoring.
  • Improving model deployment workflows, focusing on minimizing latency, ensuring reproducibility, and enabling fast iterations.

In our collaborative team made up of passionate quantitative researchers, you'll get instant validation of your work and experience short feedback cycles, where going from inception to deployment can be a matter of hours. You'll take ownership of your projects, prioritize your work, and choose the tools that get the job done.

About the Team:

We're a tight-knit modeling team with PhDs and MScs covering multiple nationalities, expertise in statistical analysis, mathematical modeling, and machine learning. We value technical discussions and encourage collaboration. We work alongside software developers and traders who implement and conceive mathematical models together with us.

About You:

  • Fluency with computer science fundamentals – data structures and algorithms.
  • Experience working with out-of-core datasets and training distributed models.
  • Proficiency in Python, especially data preprocessing, ETL pipelines, and distributed systems.
  • Familiarity with strongly typed languages like C# or C/C++ or Rust.
  • Experience with the full Machine Learning stack from data generation through model training and validation.
  • Experience with distributed computing frameworks (e.g., Spark, Ray, or Dask).

Nice to Have:

  • A scientific and inquisitive mind.
  • Experience working with popular ML frameworks like PyTorch, Tensorflow, XGBoost, and/or Catboost.
  • Familiarity with algorithmic trading concepts.
  • PhD or MSc degree in engineering, computer science, mathematics, or physics.

We offer a flat hierarchy, high levels of trust and autonomy, exciting problems to solve, a collaborative team, and great benefits.