record of scientific software development, including data acquisition and/or data analysis. (S&I) Experience developing well-designed, robust software in Python and its scientific packages (such as numpy, scipy, matplotlib, pandas). (S&I) Understanding of modern software development practices (e.g. testing, version control, continuous integration, Agile, object-oriented design). (S&I) Experience of leading software projects More ❯
Milton Keynes, Buckinghamshire, South East, United Kingdom Hybrid / WFH Options
LA International Computer Consultants Ltd
of Bedrock, Sagemaker, Python and Pandas. Key Responsibilities: * Working experience LLMs under Bedrock and Sagemaker both Amazon * Python with APIs to ChatGPT * Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Key Skills & Experience: AWS Data Science Environment: Hands-on experience with Sage Maker, Lambda, Step Functions, S3, Athena. Model deployment and pipeline orchestration … Use-Case Development: Proficiency with Amazon Tex-tract, Tesseract, and LLM-based OCR. Building document parsing pipelines, validations, and rule Python Proficiency: Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Writing clean, modular, and testable code. Traditional Machine Learning Models: Experience with regression (linear, ridge), classification (logistic regression, decision trees, random forests), clustering More ❯
Deployment: ship a model as a container, update an Airflow (or Azure Data Factory) job. Review: inspect dashboards, compare control vs. treatment, plan next experiment. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow)SQL (Redshift, Snowflake or similar)AWS SageMaker Azure ML migration, with Docker, Git, Terraform, Airflow/ADFOptional extras: Spark, Databricks, Kubernetes. What you'll bring More ❯
experience and Vector DB experience * Proven experience in time series analysis and forecasting, preferably in a commercial or industrial setting. * Strong proficiency in Python, including libraries such as Pandas, NumPy, and scikit-learn for data manipulation and modelling. * Experience with machine learning algorithms. * Proficient in data visualization techniques to effectively communicate insights from time series data. * Strong problem-solving skills More ❯
