201 to 225 of 284 Pandas Jobs in England

to computer vision challenges Knowledgeable about key architectures like Vision Transformers, DeepLabv3, and SegFormer Proficient in Python and ML tools, including Scikit-Learn, NumPy, Pandas, PyTorch, TensorFlow, or Keras Capable of applying machine learning to solve real-world problems Please apply via the link for immediate consideration More ❯

kit learn, tensorflow, metaflow, MLOps) Preferred Experience: Knowledge of Rust Experience with frameworks like Metaflow, Prefect, etc. Experience with geospatial libraries i.e. Raster, Geo-pandas, Vector databases This role would see you work in their South West office c.1 - 2 days per week ideally. It is available immediately for an More ❯

kit learn, tensorflow, metaflow, MLOps) Preferred Experience: Knowledge of Rust Experience with frameworks like Metaflow, Prefect, etc. Experience with geospatial libraries i.e. Raster, Geo-pandas, Vector databases This role would see you work in their South West office c.1 - 2 days per week ideally. It is available immediately for an More ❯

such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science More ❯

such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science More ❯

learning applications such as recommendation systems, segmentation, and marketing optimisation. Proficiency in Python, SQL, Bash, and Git, with hands-on experience in Jupyter notebooks, Pandas, and PyTorch. Familiarity with cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong problem-solving skills and a passion for driving measurable More ❯

such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science More ❯

of transfer learning and popular augmentation techniques Able to apply machine learning to real-life problems Vision Transformers, DeepLabv3, SegFormer, etc.Python, Scikit-Learn, NumPy, Pandas and PyTorch/TensorFlow/Keras Thrive in a cross-functional working environment Possess a clear passion for data science beyond the day job Nice More ❯

learning applications such as recommendation systems, segmentation, and marketing optimisation. Proficiency in Python, SQL, Bash, and Git, with hands-on experience in Jupyter notebooks, Pandas, and PyTorch. Familiarity with cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong problem-solving skills and a passion for driving measurable More ❯

mindset. Proven track record with NLP applications and transformer-based models like BERT or GPT. Advanced proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or More ❯

mindset. Proven track record with NLP applications and transformer-based models like BERT or GPT. Advanced proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or More ❯

track record of delivering impactful projects. Strong statistical and machine learning expertise, with the ability to apply and evaluate various algorithms. Proficiency in Python (Pandas), SQL, and data analytics tools. Experience deploying and evaluating ML models in production environments. Ability to interpret complex datasets, drawing meaningful insights to drive business More ❯

track record of delivering impactful projects. Strong statistical and machine learning expertise, with the ability to apply and evaluate various algorithms. Proficiency in Python (Pandas), SQL, and data analytics tools. Experience deploying and evaluating ML models in production environments. Ability to interpret complex datasets, drawing meaningful insights to drive business More ❯

and other teams. Required Skills: Python: Strong knowledge of libraries related to service development such as PyNum, boto3, PyTest, Kafka, RabbitMQ, etc. Knowledge of pandas is a plus. AWS: Experience with AWS services like Lambda, S3, ECS, SNS, SQS, CloudWatch, Kinesis for application development. Databases: Experience with NoSQL databases (MongoDB More ❯

CI pipelines. Requirements 2-5 years of experience in market risk, preferably within crypto, fintech, derivatives trading, or digital asset exchanges. Proficiency in Python (pandas, NumPy, matplotlib) for analytics and tool development. Experience with SQL and handling large structured/unstructured datasets. Familiarity with Git/GitHub and collaborative development More ❯

to the founding members, and you’ll be given ownership on the direction of data engineering across the business. They’re currently using Python (Pandas), PostgreSQL, on AWS as the core technologies within data engineering, but you’ll also work on some exciting AI projects. If you feel there’s More ❯

in this role, a candidate must possess the following attributes: Well versed in Python and SQL. Experience with Python libraries such as SciKit Learn, Pandas, Numpy are highly desirable. Experience with deep learning frameworks such as Pytorch or Tensorflow Understanding the full data science project life cycle, from initial problem More ❯

to the founding members, and you’ll be given ownership on the direction of data engineering across the business. They’re currently using Python (Pandas), PostgreSQL, on AWS as the core technologies within data engineering, but you’ll also work on some exciting AI projects. If you feel there’s More ❯

experience in translating technical methods to non-technical stakeholders Strong programming experience in python (R, Python, C++ optional) and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain) Experience with version control (GitHub) ML experience with causality, Bayesian statistics & optimization, survival More ❯

software development experience, with a proven ability to work independently and innovate. Proficiency in Python, particularly for numerical computing and machine learning Particularly numpy, pandas (both must haves) Good working knowledge of a fast language such as C/C++/Rust. Understanding of production-level system design and architecture. More ❯

software development experience, with a proven ability to work independently and innovate. Proficiency in Python, particularly for numerical computing and machine learning Particularly numpy, pandas (both must haves) Good working knowledge of a fast language such as C/C++/Rust. Understanding of production-level system design and architecture. More ❯

or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or Engineering - or equivalent. Proficiency in Python and relevant data science libraries (NumPy, pandas, scikit-learn, etc.). Experience with SQL, Power BI, Git & GitHub. Strong knowledge of Machine Learning Algorithms and respective theory. Ability to work within a More ❯

Experience working within a variety of development frameworks and practices e.g. DevOps, DevSecOps, SCRUM, MLOps, XP. Experience with data analysis and manipulation tools (e.g. Pandas) Experience of a broad section of the Software Development Lifecycle (SDLC) with specific focus on: Design(Architecting, High-Level Design and Low-Level Design) Development More ❯

Experience working within a variety of development frameworks and practices e.g. DevOps, DevSecOps, SCRUM, MLOps, XP. Experience with data analysis and manipulation tools (e.g. Pandas) Experience of a broad section of the Software Development Lifecycle (SDLC) with specific focus on: Design(Architecting, High-Level Design and Low-Level Design) Development More ❯

Experience working within a variety of development frameworks and practices e.g. DevOps, DevSecOps, SCRUM, MLOps, XP. Experience with data analysis and manipulation tools (e.g. Pandas) Experience of a broad section of the Software Development Lifecycle (SDLC) with specific focus on: Design(Architecting, High-Level Design and Low-Level Design) Development More ❯