9 of 9 DemandTrendContract scikit-learn Jobs

deploying productionised Machine Learning applications on a cloud platform (GCP ideal, AWS & Azure also acceptable) * Experience with common Python packages for Machine Learning - examples include PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas, etc. * Strong knowledge of SQL and its use for data preparation & feature engineering * Understanding of & practical experience with implementing MLOps principals - including automated model retraining More ❯

Bring: 3+ years' experience building and deploying ML models, ideally in NLP or computer vision domains. Expert-level Python and SQL, with solid experience using libraries like Pandas, Scikit-Learn, TensorFlow, etc. Proven experience working with BigQuery and big data pipelines on GCP . Deep understanding of statistics, machine learning algorithms, and data modelling. Strong analytical mindset with More ❯

Bring: 3+ years' experience building and deploying ML models, ideally in NLP or computer vision domains. Expert-level Python and SQL, with solid experience using libraries like Pandas, Scikit-Learn, TensorFlow, etc. Proven experience working with BigQuery and big data pipelines on GCP . Deep understanding of statistics, machine learning algorithms, and data modelling. Strong analytical mindset with More ❯

be joining a small, agile team working on projects ranging from genomic data interpretation to clinical trial optimization . Key Responsibilities: Build and deploy ML models using Python , scikit-learn , and PyTorch Work with structured and unstructured biomedical datasets (e.g. genomic sequences, patient records, imaging) Collaborate with bioinformaticians and clinical researchers to translate data into actionable insights Contribute More ❯

Azure services, especially Azure Machine Learning, Azure Kubernetes Service (AKS), Azure Data Lake, and Azure Synapse, Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn, Strong understanding of MLOps concepts, including continuous integration/continuous, deployment (CI/CD) for ML, model versioning, monitoring, and retraining, Proficiency with Scripting and programming languages (Python More ❯

will have a proven commercial experience delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. More ❯

data scientists to build and deploy production-level solutions Troubleshoot and debug code Work with other teams to understand and solve business problems About you: Python (pandas, NumPy, scikit-learn): For data wrangling, modelling, and feature engineering SQL: For querying structured data sources Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models Machine More ❯

a commercial or trading environment Proficiency in time series analysis, regression modelling, and forecasting techniques Strong experience with Python and core libraries for data science (e.g., pandas, NumPy, scikit-learn, statsmodels) Ability to manipulate and analyse large, complex datasets with attention to detail Clear, confident communicator who can explain analytics and influence commercial decisions Experience using visualisation tools More ❯

business. Machine Learning Engineer, key skills: Significant experience working as a Data Scientist/Machine Learning Engineer Solid knowledge of SQLandPython's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib). GCP, VertexAI experience is desirable (developing GCP machine learning services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software More ❯