1 to 25 of 59 Remote Permanent Pandas Jobs

managers, and async/await patterns - Data structures and algorithms for efficient data processing and model optimization - Error handling and debugging using try-catch blocks, logging, and debugging tools - Pandas and NumPy for data manipulation, cleaning, and numerical operations - SQLAlchemy or psycopg2 for database connectivity and ORM operations - Boto3 for AWS service integration and automation - Lambda function development with proper More ❯

managers, and async/await patterns - Data structures and algorithms for efficient data processing and model optimization - Error handling and debugging using try-catch blocks, logging, and debugging tools - Pandas and NumPy for data manipulation, cleaning, and numerical operations - SQLAlchemy or psycopg2 for database connectivity and ORM operations - Boto3 for AWS service integration and automation - Lambda function development with proper More ❯

managers, and async/await patterns - Data structures and algorithms for efficient data processing and model optimization - Error handling and debugging using try-catch blocks, logging, and debugging tools - Pandas and NumPy for data manipulation, cleaning, and numerical operations - SQLAlchemy or psycopg2 for database connectivity and ORM operations - Boto3 for AWS service integration and automation - Lambda function development with proper More ❯

DynamoDB, etc.). Skilled with Docker and container management. Strong software engineering background : code reviews, version control, optimisation, testing, and logging. Expertise in machine learning libraries such as NumPy, Pandas, TensorFlow, PyTorch, SciPy, and Dask. Proven experience linking data from multiple systems to create scalable solutions. Knowledge of cloud security best practices and experience with DevOps life cycles . Desirable More ❯

DynamoDB, etc.). Skilled with Docker and container management. Strong software engineering background : code reviews, version control, optimisation, testing, and logging. Expertise in machine learning libraries such as NumPy, Pandas, TensorFlow, PyTorch, SciPy, and Dask. Proven experience linking data from multiple systems to create scalable solutions. Knowledge of cloud security best practices and experience with DevOps life cycles . Desirable More ❯

engineers and contribute to best practices across the team. Key skills: Strong experience with AWS data services (S3, Redshift, Glue, Lambda, Lake Formation, CloudFormation). Proficiency in SQL, Python (Pandas), Spark or Iceberg. Experience with data warehouse design, ETL/ELT, and CI/CD pipelines (GitHub, CodeBuild). Knowledge of infrastructure as code, performance tuning, and data migration. Exposure More ❯

engineers and contribute to best practices across the team. Key skills: Strong experience with AWS data services (S3, Redshift, Glue, Lambda, Lake Formation, CloudFormation). Proficiency in SQL, Python (Pandas), Spark or Iceberg. Experience with data warehouse design, ETL/ELT, and CI/CD pipelines (GitHub, CodeBuild). Knowledge of infrastructure as code, performance tuning, and data migration. Exposure More ❯

vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working with More ❯

vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working with More ❯

vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working with More ❯

vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working with More ❯

vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working with More ❯

validation techniques such as cross-validation, bootstrapping, and assessing the statistical significance of model improvements. Excellent knowledge of data analysis, visualization, and preprocessing techniques. Familiarity with tools such as Pandas, NumPy, and Matplotlib. Experience deploying Classical and Modern Time Series Forecasting solutions using tools such as Neural Prophet, SARIMA, Chronos, etc Familiar with cloud-based machine learning platforms such as More ❯

meaningful insights from structured and unstructured datasets of varying sizes. Track record of implementing impactful models that drive sustained business results. Proficiency in the Python data science tech stack (pandas, scikit-learn, NumPy, and visualisation libraries) Experience working in a Linux-based cloud environment (e.g. GCP, Azure, AWS). Experience using git version control. Communication, stakeholder management, and problem-solving More ❯

Familiarity with data pipeline orchestration and a strong grasp of DevSecOps best practices in cloud-native environments • Hands-on experience with key tools and frameworks, including: o Python, NumPy, Pandas, scikit-learn o TensorFlow or PyTorch o Elasticsearch, Logstash, Kibana • Preferred Experience in GDS (Government Digital Services) or USDS (U.S. Digital Services) Education Requirement • Shall have at a minimum, a More ❯

Proven hands-on expertise with GCP services (BigQuery, Cloud Storage, Dataflow) Proficiency in Power BI for creating reports and dashboards Strong Python skills, including experience with data libraries like Pandas and NumPy Solid background in ETL processes, data pipeline design, and data warehousing Detail-oriented with excellent problem-solving and communication skills Nice to Have: Knowledge of data governance, quality More ❯

Proven hands-on expertise with GCP services (BigQuery, Cloud Storage, Dataflow) Proficiency in Power BI for creating reports and dashboards Strong Python skills, including experience with data libraries like Pandas and NumPy Solid background in ETL processes, data pipeline design, and data warehousing Detail-oriented with excellent problem-solving and communication skills Nice to Have: Knowledge of data governance, quality More ❯

Required Skills & Experience: Bachelor's degree in Computer Science, Mathematics, Statistics, Business Administration or related field Advanced knowledge of SQL Good knowledge of Python, including popular Data Science packages (pandas, matplotlib, seaborn, numpy, sklearn) Familiarity with what is happening under the hood of popular Machine Learning algorithms Strong problem-solving skills and attention to detail Strong communication and collaboration skills More ❯

with engineers and writing actionable JIRA/ADO tickets. Nice to have: SQL for analysis (e.g., BigQuery/Looker) and basic data QA. Python for automation/log parsing (pandas, requests) and Search Console API usage. International SEO experience (hreflang, ccTLD/subfolder strategies). Experience with A/B testing and measurement frameworks. How to Apply Send your CV More ❯

recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modelling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (eg pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model life cycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure More ❯

learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from More ❯

or similar domains with forecasting needs. Skills and competencies Essential: Experience working with Python or R in a production or research setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational More ❯

or similar domains with forecasting needs. Skills and competencies Essential: Experience working with Python or R in a production or research setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational More ❯