51 to 75 of 278 Permanent Pandas Jobs

solutions Broad experience across multiple ML domains, including: Forecasting/Time-Series Modelling Regression Classification Gradient Boosting models (e.g. XGBoost, LightGBM) Strong Python skills (Pandas, NumPy, scikit-learn, PyTorch) Experience with model evaluation, performance monitoring, and accuracy metrics Version control (Git) Experience working with cloud environments (Azure preferred, AWS/ ...

learning, time series forecasting, reinforcement learning, optimization, or conversational AI. Familiarity with Python and common AI/ML frameworks (e.g. TensorFlow, PyTorch, scikit-learn, Pandas, NumPy). Software engineering fundamentals — version control, code review, modular design, and writing testable code intended for someone else to run in production. Strong analytical ...

applications using Python or/and Go/RustExcellent Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualization and API libraries (matplotlib, plotly, streamlit, Flask, etc).Experience developing and implementing Machine learning models ...

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 ...

scalable SaaS platform. Any other ad hoc duties that may be required from time to time Technical Requirements: Proven experience with Python, especially Pandas and NumPy Mastery of SQL and PostgreSQL: schema design, complex queries, indexing and performance optimisation, beyond basic querying Experience with pipeline orchestration and scheduling Proven ability ...

CROs: data transfers, EDC extracts, visit structures and database lock Strong Python skills gained in a commercial setting, including the scientific Python stack e.g. pandas, NumPy, pandera and pytest Experience building and maintaining production data pipelines with automated testing and CI/CD Experience implementing data validation and quality checks ...

CROs: data transfers, EDC extracts, visit structures and database lock Strong Python skills gained in a commercial setting, including the scientific Python stack e.g. pandas, NumPy, pandera and pytest Experience building and maintaining production data pipelines with automated testing and CI/CD Experience implementing data validation and quality checks ...

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/ ...

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 ...

architecture, and security teams to ensure platform access and data privacy. Key Skills and Requirements: Proficiency in production-quality Python (e.g., FastAPI, Pydantic, asyncio, pandas, pytest). Experience with R and R Shiny for building and deploying applications. Hands-on expertise with LLM APIs (e.g., OpenAI, Anthropic Claude) and agent ...

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 ...

technologies and identify opportunities to improve business efficiency through intelligent automation. Skills & Experience Strong Python programming skills with experience using libraries such as Pandas, NumPy, Scikit-learn, XGBoost or LightGBM, and Plotly, Rust, Typescript, Python or Matplotlib. Experience developing machine learning models for prediction, optimisation or classification. Strong SQL skills ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 - Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 - AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

software testing and test automation. An introduction to data science, including data analysis, statistics and visualisation. Training in Python and tools such as NumPy, Pandas and PyTest. An introduction to AI and Machine Learning, including LLMs, SLMs and traditional ML models. Specialist training in AI testing, model performance, data quality ...

software testing and test automation. An introduction to data science, including data analysis, statistics and visualisation. Training in Python and tools such as NumPy, Pandas and PyTest. An introduction to AI and Machine Learning, including LLMs, SLMs and traditional ML models. Specialist training in AI testing, model performance, data quality ...

Python; experience with R and/or C/C++ is a strong plus Extensive experience with numerical and data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar) Proven experience building or maintaining machine learning systems in a distributed computing environment Proficiency developing in a Linux ...

Tables, Databricks Workflows, or similar data orchestration and governance capabilities. Strong Python proficiency and experience with data engineering libraries and frameworks such as PySpark, Pandas, and Pydantic. Experience with Infrastructure as Code tools such as Terraform, OpenTofu, AWS CDK, or CloudFormation. AWS and/or Databricks certifications, such ...

Excellent communication skills with the ability to communicate concepts clearly and precisely Experience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) databases; and iii) cloud platform services (AWS, GCP, Azure) NICE TO HAVES Experience as a Data Architect or Senior Manager Proven track record ...

strong foundation in system design, data storage, and reliability with commonly used data platforms (Databricks, Snowflake, BigQuery, PSQL, etc.) and data engineering tools (e.g., Pandas, Spark, dbt, etc.) Hands-on experience with MLOps/LLMOps principles, including CI/CD for data workflows, automated agent evaluation (LangSmith, Opik, Langfuse ...

programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data ...

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 ...

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 ...