1 to 25 of 112 Remote/Hybrid Permanent Pandas Jobs

Machine Learning Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker ...

MLflow, Kubeflow, Vertex AI, or similar technologies. Knowledge of workflow orchestration platforms such as Apache Airflow. Experience with data processing technologies such as Pandas, Apache Beam, Spark, or similar frameworks. Strong SQL skills and experience with analytical databases such as BigQuery, PostgreSQL, or ClickHouse. Familiarity with observability and monitoring tools ...

world problems. Experience of coaching junior data scientists/analysts. Experience in reviewing code and documentation to a high standard. Experience in using Python (pandas, numpy, scikit-learn). End-to-end experience of managing multiple data science and analytics projects in different industries and with different types of data ...

solutions to real-world problems.Experience of coaching junior data scientists/analysts.Experience in reviewing code and documentation to a high standard.Experience in using Python (pandas, numpy, scikit-learn).End-to-end experience of managing multiple data science and analytics projects in different industries and with different types of data (text ...

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 ...

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 ...

Working You’ll work in a modern data and machine learning environment. The role is likely to involve: Python, including libraries such as Pandas, NumPy and scikit‐learn. SQL and large structured datasets. Cloud data platforms such as Snowflake, Databricks or similar. Git‐based version control and code review. ...

Computer Science, Mathematics, Statistics or another STEM-related discipline. Desirable Skills Experience with cloud platforms such as AWS, Azure or GCP . Experience with Pandas, NumPy and Scikit-learn . Knowledge of data visualisation tools such as Power BI or Tableau. Experience with Git/version control. Exposure to Generative ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem-solving. Technical Expertise & Tools Python: Advanced, production-grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem‐solving. Technical Expertise & Tools Python: Advanced, production‐grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem-solving. Technical Expertise & Tools : Python: Advanced, production-grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem-solving. Technical Expertise & Tools : Python: Advanced, production-grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem-solving. Technical Expertise & Tools : Python: Advanced, production-grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...