23 of 23 NumPy Jobs in the South West

around imbalance exposure, generation patterns, demand profiles, and commercial optimisation. Required Skills and Experience Technical Skills Proficiency in Python and associated data science libraries (NumPy, Pandas, SciPy, scikit‐learn, PyTorch/TensorFlow). Strong experience with time‐series modelling (ARIMA, Prophet, LSTMs or similar). Understanding of optimisation methods (linear ...

around imbalance exposure, generation patterns, demand profiles, and commercial optimisation. Required Skills and Experience Technical Skills Proficiency in Python and associated data science libraries (NumPy, Pandas, SciPy, scikit‐learn, PyTorch/TensorFlow). Strong experience with time‐series modelling (ARIMA, Prophet, LSTMs or similar). Understanding of optimisation methods (linear ...

around imbalance exposure, generation patterns, demand profiles, and commercial optimisation. Required Skills and Experience Technical Skills Proficiency in Python and associated data science libraries (NumPy, Pandas, SciPy, scikit‐learn, PyTorch/TensorFlow). Strong experience with time‐series modelling (ARIMA, Prophet, LSTMs or similar). Understanding of optimisation methods (linear ...

around imbalance exposure, generation patterns, demand profiles, and commercial optimisation. Required Skills and Experience Technical Skills Proficiency in Python and associated data science libraries (NumPy, Pandas, SciPy, scikit‐learn, PyTorch/TensorFlow). Strong experience with time‐series modelling (ARIMA, Prophet, LSTMs or similar). Understanding of optimisation methods (linear ...

your 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 ...

working and technical knowledge of GCP (GCS Buckets, BigQuery, Dataproc, Pub/Sub), Airflow, Spark, PySpark, Spark SQL, Hive. Good knowledge of Python (Pandas, NumPy, Wiresafe), SQL, Linux CLI, BigQuery. Experience with DBMS, Delta Tables, Oracle, MS Access, SQL Server. Skills in Data Modelling, ETL/ELT Data Pipelines, Python ...

working and technical knowledge of GCP (GCS Buckets, BigQuery, Dataproc, Pub/Sub), Airflow, Spark, PySpark, Spark SQL, Hive. Good knowledge of Python (Pandas, NumPy, Wiresafe), SQL, Linux CLI, BigQuery. Experience with DBMS, Delta Tables, Oracle, MS Access, SQL Server. Skills in Data Modelling, ETL/ELT Data Pipelines, Python ...

working and technical knowledge of GCP (GCS Buckets, BigQuery, Dataproc, Pub/Sub), Airflow, Spark, PySpark, Spark SQL, Hive. Good knowledge of Python (Pandas, NumPy, Wiresafe), SQL, Linux CLI, BigQuery. Experience with DBMS, Delta Tables, Oracle, MS Access, SQL Server. Skills in Data Modelling, ETL/ELT Data Pipelines, Python ...

working and technical knowledge of GCP (GCS Buckets, BigQuery, Dataproc, Pub/Sub), Airflow, Spark, PySpark, Spark SQL, Hive. Good knowledge of Python (Pandas, NumPy, Wiresafe), SQL, Linux CLI, BigQuery. Experience with DBMS, Delta Tables, Oracle, MS Access, SQL Server. Skills in Data Modelling, ETL/ELT Data Pipelines, Python ...

working and technical knowledge of GCP (GCS Buckets, BigQuery, Dataproc, Pub/Sub), Airflow, Spark, PySpark, Spark SQL, Hive. Good knowledge of Python (Pandas, NumPy, Wiresafe), SQL, Linux CLI, BigQuery. Experience with DBMS, Delta Tables, Oracle, MS Access, SQL Server. Skills in Data Modelling, ETL/ELT Data Pipelines, Python ...

working and technical knowledge of GCP (GCS Buckets, BigQuery, Dataproc, Pub/Sub), Airflow, Spark, PySpark, Spark SQL, Hive. Good knowledge of Python (Pandas, NumPy, Wiresafe), SQL, Linux CLI, BigQuery. Experience with DBMS, Delta Tables, Oracle, MS Access, SQL Server. Skills in Data Modelling, ETL/ELT Data Pipelines, Python ...

Mathematics, Engineering, or a related field 0–1 years of experience in data analysis or data science (internships included) Strong foundation in Python (Pandas, NumPy, Scikit-learn) or R Basic understanding of statistical analysis and machine learning concepts Experience working with SQL and relational databases Familiarity with data visualisation tools ...

Strong python development experience, able to follow PEP8 standards Experience of developing GIS pipelines in python, leveraging open source libraries such as Fiona, Shapely, Numpy and Rasterio Ability to communicate effectively, explaining and rationalizing design decisions to a cross functional team. Experience in object-oriented programming concepts, unit & integration testing ...

your 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 ...

your 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 ...

your 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 ...

your 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 ...

concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able to iterate quickly ...

concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able to iterate quickly ...

concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able to iterate quickly ...

concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able to iterate quickly ...

concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able to iterate quickly ...

concepts: dataset splits, overfitting, evaluation metrics, augmentation, and performance trade-offs. Comfortable working with image processing and common computer vision libraries (e.g., OpenCV, NumPy, Pillow, SciPy, Matplotlib). Good engineering habits: Git-based workflows, virtual environment usage, clean code, and reproducible experiments. Strong problem-solving ability, able to iterate quickly ...