technical stakeholders. Tools/Frameworks : PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with More ❯
in Bedrock, Sagemaker, Python, and Pandas. Key Responsibilities: Working experience with LLMs under Bedrock and Sagemaker (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 SageMaker, Lambda, Step Functions, S3, Athena. Model deployment and pipeline orchestration in … AWS. OCR Use-Case Development: Proficiency with Amazon Textract, Tesseract, and LLM-based OCR. Building document parsing pipelines, validations, and rules. Python Proficiency: Strong skills with libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Ability to write clean, modular, and testable code. Traditional Machine Learning Models: Experience with regression (linear, ridge), classification (logistic regression, decision trees, random More ❯
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 ❯
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 ❯
Milton Keynes, Buckinghamshire, South East, United Kingdom
Stott & May Professional Search Limited
AWS Data Science Tools: Hands-on with SageMaker, Lambda, Step Functions, S3, Athena. - OCR Development: Experience with Amazon Textract, Tesseract, and LLM-based OCR. - Python Expertise: Skilled in Pandas, NumPy, scikit-learn, PyTorch, Hugging Face Transformers; modular, testable code. - ML Models: Proficient in regression, classification, clustering, and time-series forecasting. - Business Insight: Translate business needs into data-driven solutions and More ❯
standards and discipline. Manage quarterly appraisal processes and documentation. Experience & Qualities Degree in a mathematical or computing discipline or equivalent. Over 2 years’ experience with production-level Python, including numpy, pandas, sklearn. Strong understanding of machine learning algorithms, workflows, and projects like recommender systems. Experience with containerised deployment (Docker) and CI/CD processes. Proficient in SQL and Microsoft Office. More ❯