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Python
The default language for data science, machine learning, and backend API development. Its ecosystem covers the full pipeline from data ingestion to model serving.
Trusted by leading organisations
The default language for data science, machine learning, and backend API development. Its ecosystem covers the full pipeline from data ingestion to model serving.
Trusted by leading organisations
Python bridges the gap between data science and software engineering. With type hints, async/await, and frameworks like FastAPI, Python has matured beyond scripting into a language for building production services.
The ecosystem spans pandas and scikit-learn for data work, PyTorch and TensorFlow for ML, and FastAPI for high-performance APIs. The challenge is writing Python that scales in performance, team size, and operational reliability.
Technology snapshot
Current industry demand for this technology
How widely used by development teams worldwide
How well it handles growth in load and complexity
At a glance
Build documented, validated APIs with Python type hints and Pydantic. Async support handles high-concurrency workloads.
Production data pipelines using Airflow or Prefect for orchestration, dbt for transformation, and pandas or Polars for processing.
Serve ML models in production with BentoML or Ray Serve. Orchestrate prompt chains and retrieval pipelines for LLM applications.
Data pipelines for ASX-listed companies processing market data, risk calculations, and regulatory reporting.
Strict typing with mypy, src layout, and Ruff for linting. We treat Python with the same rigour as statically typed languages.
Models move from Jupyter notebooks to containerised serving endpoints with CI/CD, model versioning, and regression testing.
High-concurrency Python services with FastAPI, asyncio, and proper connection pooling.
Engineers who understand both the data domain and software engineering. Not just one or the other.
Python-based AI products using LangChain, Claude API, and OpenAI. First-hand production AI experience from our own tools.
Talk to our Python engineers about data pipeline architecture, FastAPI service design, or ML model deployment.
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