151 to 175 of 369 Pandas Jobs in the UK

Requirements Essential Expert Python, with deep hands‐on PyTorch experience (TensorFlow also welcome) and the surrounding ecosystem: Hugging Face Transformers, timm, scikit‐learn, NumPy, pandas, OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking and model versioning with MLflow ...

Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib) Strong software development skills (Python is the preferred language) Proven experience in deploying ML/AI services suing Kubernetes & KubeFlow Strong management ...

need everything) Experience of working in an Agile delivery team Strong analytic skills related to working with unstructured datasets Python (PySpark, Pandas, PyArrow) Distributed data processing (Apache Spark) Data ETL (Apache Airflow, AWS Step Functions, Apache NiFi) Cloud services (AWS, Azure or GCP) Messaging/Streaming (Kafka, AWS SQS, Other ...

need everything) Experience of working in an Agile delivery team Strong analytic skills related to working with unstructured datasets Python (PySpark, Pandas, PyArrow) Distributed data processing (Apache Spark) Data ETL (Apache Airflow, AWS Step Functions, Apache NiFi) Cloud services (AWS, Azure or GCP) Messaging/Streaming (Kafka, AWS SQS, Other ...

Statistics or Maths.* Strong Python coding experience/knowledge essential. Knowledge of git and CI/CD practices. Demonstrable proficiency with packages such as Pandas, Sklearn; Pytorch or Keras.* Knowledge of SQL and Excel; experience with Databricks would be welcome.**Person specification*** Excellent analytical skills and attention to detail.* Works ...

computational techniques. Proficiency in Python for data analysis and machine learning. Strong understanding of statistical methods, data manipulation, and data visualisation libraries (e.g., pandas and NumPy, scikit-learn, PyTorch, matplotlib/plotly). Utilise process/data analysis techniques to assess the potential of existing processes and propose alternative production ...

Requirements Essential Expert Python, with deep hands‐on PyTorch experience (TensorFlow also welcome) and the surrounding ecosystem: Hugging Face Transformers, timm, scikit‐learn, NumPy, pandas, OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking and model versioning with MLflow ...

strength in an area such as predictive modelling, classification, regression, optimisation or recommendation systemsStrong proficiency in Python and open-source data libraries such as Pandas, NumPy and Scikit-learnA solid grounding in statistical methodologies, along with data extraction, manipulation and feature engineering techniquesExperience with Spark, agile delivery methods ...

version control. Strong understanding of algorithms, data structures, and software design principles. Familiarity with data manipulation and analysis tools such as Pandas, NumPy, and SQL. Experience across the Power Platform, including Power Apps, Power Automate, Power Pages and Dataverse, together with solution management, environments and application lifecycle management. Experience building ...

Strong understanding of OOP concepts, design patterns, SOLID principles, algorithms, data structures, and ability to write clean, maintainable code Backend Development – Proficiency in Python (Pandas, FastAPI, Flask) for building enterprise applications, data processing, and API development Frontend Development – Experience with ReactJS, Node.js, TypeScript/JavaScript, and modern web development practices ...

async Python frameworks) Strong working knowledge of modern machine learning — able to understand, integrate, and extend the functionality of an ML library (NumPy, SciPy, Pandas, and frameworks such as scikit-learn or PyTorch) Understanding of core ML concepts — model training, evaluation, and production trade-offs — enough to design robust interfaces ...

What we’re looking for: Proficiency in Python (and at least one other language a plus). Experience with key libraries such as PyTorch, Pandas, Hugging Face Transformers, or similar AI toolkits. Working knowledge of common models, and their use cases and experience applying them to solve specific problems. Solid ...

data analyst or similar role. Strong SQL skills, including complex joins, aggregations and window functions. Proficiency in Python for data analysis (e.g., pandas, NumPy). Hands‐on experience with at least one cloud data platform: Databricks, AWS or Snowflake. Strong analytical and problem‐solving skills, with close attention to detail. ...

memory management, and interoperability protocols such as MCP Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit-learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model and machine learning workloads with ...

automation across the organisation. You should have a strong foundation in programming (Python or R), with experience using data science libraries such as pandas, scikit-learn or similar. A good understanding of statistical methods and machine learning concepts is essential. Experience working with SQL and handling data in cloud ...

version control. Strong understanding of algorithms, data structures, and software design principles. Familiarity with data manipulation and analysis tools such as Pandas, NumPy, and SQL. Experience across the Power Platform, including Power Apps, Power Automate, Power Pages and Dataverse, together with solution management, environments and application lifecycle management. Experience building ...

async Python frameworks) Strong working knowledge of modern machine learning — able to understand, integrate, and extend the functionality of an ML library (NumPy, SciPy, Pandas, and frameworks such as scikit-learn or PyTorch) Understanding of core ML concepts — model training, evaluation, and production trade-offs — enough to design robust interfaces ...

Requirements Essential Expert Python, with deep hands-on PyTorch experience (TensorFlow also welcome) and the surrounding ecosystem: Hugging Face Transformers, timm, scikit-learn, NumPy, pandas, OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking and model versioning with MLflow ...

party packagesExperience leading design of large-scale, efficient and performant analytics workflows, including ETL, orchestration, and distributed compute, using industry-standard libraries such as Pandas, Polars, and Dask. Experience with both SQL and NoSQL database platforms, as well as OLAP and OLTP databasesAn understanding of data structures and common data ...

data transformation methodologiesExperience contributing to large-scale, efficient and performant analytics workflows, including ETL, orchestration, and distributed compute, using industry-standard libraries such as Pandas, Polars, and Dask. Experience working in a modern software engineering environment leveraging Agile (Scrum), DevSecOps methodologies, CI/CD workflows, and tools including ...

Excellent English and strong presentation skills Experience with Microsoft PowerPoint and Excel Preferred Qualifications Programming skills in Python including data science libraries such as pandas, numpy or plotly Work experience in: Consulting or a client-facing business Quantitative research methods (especially surveys and experiments) Media and conversation analysis Expertise ...

particularly in AWS environments, using infrastructure-as-code tools (such as Terraform, CloudFormation, or Pulumi)Experience with data manipulation and analysis tools (such as Pandas or SQL) for processing high-volume security telemetry and creating sophisticated automation triggersAdditional Preferred Qualifications: Experience with Google SecOps platform and familiarity with integrating Agentic ...

role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferredStrong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines ...

deploy Machine Learning capabilities and techniques into other systems. Familiarity with the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit‐learn Take pride in writing clean, reusable, maintainable and well‐tested code A desire to learn and embrace new and emerging ...

with data from multiple sources and formats. Working with cloud-based data platforms, ideally Microsoft Azure. Python: core data science libraries such as numPy, pandas/polar #J-18808-Ljbffr ...