1 to 25 of 67 Remote/Hybrid Pandas Jobs in the UK

years as a Data Scientist, Hands-on experience deploying ML models to production, not just research-level familiarity, Strong proficiency in Python (NumPy, pandas, scikit-learn, matplotlib, pytorch), Understanding of Windows or Linux software development platforms Excellent command of English – both written and spoken (international client communication, presentations), Expertise ...

principles. Experience with cloud platforms (AWS, Google Cloud, Azure) and containerization technologies (Docker, Kubernetes). Familiarity with databases (SQL, NoSQL) and data processing tools (Pandas, NumPy). Soft Skills Excellent problem-solving skills. Strong communication abilities. Capability to work collaboratively in a team environment. Preferred Skills Experience with natural language ...

computer vision, machine learning, or statistical modeling, Practical experience with ML model deployment (on cloud or on-premise), Solid programming skills in Python (NumPy, pandas, scikit-learn, matplotlib, PyTorch or TensorFlow), Understanding of Windows or Linux software development platforms Good understanding of statistics and data preparation, Working knowledge ...

software engineering best practices including CI/CD, testing, version control and code quality standards. Experience with data processing and analysis tools including Pandas, NumPy, SQL and model deployment technologies such as FastAPI, ONNX or TorchScript. Soft Skills & Collaboration Strong communication skills with the ability to engage technical ...

software engineering best practices including CI/CD, testing, version control and code quality standards. Experience with data processing and analysis tools including Pandas, NumPy, SQL and model deployment technologies such as FastAPI, ONNX or TorchScript. Soft Skills & Collaboration Strong communication skills with the ability to engage technical ...

software engineering best practices including CI/CD, testing, version control and code quality standards. Experience with data processing and analysis tools including Pandas, NumPy, SQL and model deployment technologies such as FastAPI, ONNX or TorchScript. Strong communication skills with the ability to engage technical and non-technical stakeholders. Collaborative ...

more of the following technological areas: Analytics & Platform Frameworks Orchestration like Airflow or AWS Glue Database Technologies Data processing libraries & Schema Management tools like Pandas and Pydantic Storage Formats: Familiarity with data types such as JSON and Parquet DevOps and DataOps Experience of IaC tools, particularly Terraform Understanding of implementing ...

more of the following technological areas: Analytics & Platform Frameworks Orchestration like Airflow or AWS Glue Database Technologies Data processing libraries & Schema Management tools like Pandas and Pydantic Storage Formats: Familiarity with data types such as JSON and Parquet DevOps and DataOps Experience of IaC tools, particularly Terraform Understanding of implementing ...

more of the following technological areas: Analytics & Platform Frameworks Orchestration like Airflow or AWS Glue Database Technologies Data processing libraries & Schema Management tools like Pandas and Pydantic Storage Formats: Familiarity with data types such as JSON and Parquet DevOps and DataOps Experience of IaC tools, particularly Terraform Understanding of implementing ...

Linux environment Nice to have: Advanced data engineering experience in Python, e.g. with libraries like Dagster, Prefect etc Experience optimising dataframe code, e.g. in Pandas or ideally Polars Experience of machine learning techniques and related libraries and frameworks e.g. scikit-learn, Pytorch, Tensorflow etc Experience deploying and serving ML models ...

Data and Python: Python for data processing, pipelines and model serving, alongside the libraries and tooling used by our data science team (such as pandas, Polars and PySpark) What we’re looking for: Significant experience as a senior or principal engineer leading the design and delivery of data‐intensive systems ...

Linux environment Nice to have: Advanced data engineering experience in Python, e.g. with libraries like Dagster, Prefect etc Experience optimising dataframe code, e.g. in Pandas or ideally Polars Experience of machine learning techniques and related libraries and frameworks e.g. scikit-learn, Pytorch, Tensorflow etc Experience deploying and serving ML models ...

skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines ...

analytical approach. Ability to work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit‐learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review ...

Strong understanding of core ML concepts - supervised/unsupervised learning, model evaluation, feature engineering - and broad familiarity with common algorithms and architectures. Strong Python (pandas, NumPy, etc.) and SQL skills Comfortable with the standard ML toolkit: Git, Docker, scikit-learn, PyTorch or TensorFlow, and ML pipelines. Hands-on experience with ...

vector databases, and frameworks such as LangChain/LangGraph or Hugging Face. Strong Python and SQL, with working knowledge of the wider ML stack (pandas, scikit-learn, PyTorch or TensorFlow, XGBoost). Experience with cloud data and ML platforms, ideally AWS (S3, SageMaker Pipelines, Glue) and/ ...

multi-threading (-s), worker processes, memory allocators, compression algorithms, and partitioned database maintenance. Languages & Frameworks: Strong proficiency in Python (including data science stack: Pandas, NumPy, and integration tools like embedPy, PyKX, or qPython). Solid understanding of Java interface programming with KDB+ and platform Familiarity with enterprise messaging middleware (Kafka ...

cloud architectures and managing timelines, risks, and deployment roadmaps across multiple enterprise accounts . Python: Expert, production-quality Python (for example FastAPI, Pydantic, asyncio, pandas, pytest). R and R Shiny : Solid R and experience building and deploying Shiny applications. LLM and agent engineering: Hands-on experience with LLM APIs ...

delivering production-ready models that drive measurable business value. Technical Proficiency: Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (such as PyTorch, XGBoost, or LightGBM). Engineering Rigor: Proven ability to build for production. Experience working ...

stress-testing, simulation analysis, rare event modeling, and stochastic modeling preferred but not required. Substantial experience with Python, R, and relevant libraries (e.g., numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium ...

least one primary backend language: Java (Modern Java, Spring Boot, concurrency, low-latency tuning, GC optimization), OR Python (Modern Python, asynchronous programming, NumPy/Pandas, FastAPI), OR .NET/C# (Modern .NET Core, multi-threading, asynchronous I/O, memory profiling). Distributed Systems & Messaging: Strong experience with enterprise messaging ...

stress-testing, simulation analysis, rare event modeling, and stochastic modeling preferred but not required. Substantial experience with Python, R, and relevant libraries (e.g., numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium ...

good understanding of the underlying physical principles related to battery technology, electric vehicles, EV charging, and the energy sector. Python experience (numpy, streamlit, scipy, pandas, matplotlib, plotly, poetry, GIT, scikit-learn and other scientific libraries) Excellent mathematical, analytical and problem-solving ability Excellent professional communication, reporting and presentation skills Excel ...

through university projects, internships or personal projects. Experience with AWS or Google Cloud Platform. Knowledge of Docker and CI/CD concepts. Exposure to Pandas, NumPy, R or machine learning. Interest in scientific, healthcare, biotech or data-focused environments. Whether you're a recent graduate, have completed a placement year ...

least 2 years’ experience working as a data engineer (ideally consulting/financial services) – salary and level will reflect experience. Proficiency in Python (pandas, numpy) Professional experience with Azure cloud services (AWS/GCP acceptable with deeper experience) Strong experience deploying clean, maintainable, production-level code. Basic understanding ...