26 to 50 of 249 Permanent Pandas Jobs

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 ...

with Computer Vision, Deep Learning, NLP/LLM or Time-Series Analytics solutions. Strong understanding of data analysis and manipulation using tools such as Pandas, NumPy and SQL. Experience deploying AI models into operational environments. Understanding of Responsible AI principles, model explainability and AI security considerations. Experience using ...

integer programming, heuristics) Fluent in Python (required) and other programming languages (preferred) with strong skills in applying DS, ML, and OR packages (scikit‐learn, pandas, numpy, gurobi, etc.) to solve real‐life problems and visualise the outcomes (e.g., seaborn) Proficient in working with cloud platforms (AWS preferred), code versioning ...

scientists, and product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience with React (hooks, state management, component architecture) Experience building data pipelines and working with structured and unstructured data Solid understanding ...

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 ...

Proven ability to translate business problems into measurable analytical outcomes. Experience taking models from development into production environments. Python and associated data science ecosystem (Pandas, NumPy, Scikit‐learn). Machine learning techniques including classification, regression, clustering and anomaly detection. Experience with Generative AI, LLMs, RAG architectures or agent‐based ...

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 ...

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 ...

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/ ...

value What We’re Looking For Essential experience Significant experience building, training and deploying machine learning models Strong Python skills with experience using NumPy, Pandas, SciPy and modern ML frameworks such as PyTorch or TensorFlow Experience working with large-scale unstructured data Experience building and deploying production-ready NLP systems ...

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 ...

sample and genomic data. You have A BSc or MSc in computer science or related fields Expertise in Python, including popular Python libraries: NumPy, Pandas, PySpark and frameworks: Django, Django Rest Framework, FastAPI Hands-on experience with both relational (e.g. PostgreSQL) and non-relational databases (e.g. Elasticsearch, Redis) Extensive experience ...

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. ...

from concept through to production. Strong technical knowledge, including proficiency in Python and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow). Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing. Familiarity with Generative ...

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 ...

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 ...

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 ...

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 ...

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 ...