26 to 50 of 320 Pandas Jobs in England

etc. as well as hands on experience on AWS services like SageMaker and Bedrock, and programming skills such as Python, R, SQL, Java, Julia, Scala, Spark/Numpy/Pandas/scikit, JavaScript Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the More ❯

critical thinking skills to assess process efficiency and effectiveness. Technical Expertise: Advanced proficiency in Python with minimum demonstrable programming experience including data manipulation and analysis using libraries such as Pandas, NumPy, and SQLAlchemy. Extensive experience with Dash framework for building web applications. In-depth knowledge of Impala or other SQL-on-Hadoop query engines. Understanding of web development concepts (HTML More ❯

plan on securing series A funding late this year. They code in Python, and React on the Frontend. Tech & Data Science stack: Kubernetes & Docker on Google Cloud Python 3: Pandas, RabbitMQ, Celery, Flask, SciPy, NumPy, Dash, Plotly, Matplotlib Javascript, React, Redux PostgreSQL, Redis Prometheus, Alert Manager, DataDog If you joined the company in a Data Science role you would be … modelling skills but know when to be pragmatic to ensure the best business outcomes You'll be a coder in Python, C++ or Java Experience of productionizing analytics code pandas, scipy and numpy If your a Data Scientist looking to go on an exciting new journey with an early stage startup, and the opportunity to work on advanced pricing algorithms More ❯

our growing forecast offering. Developing our power market and dispatch models to grow and enhance Modo's product offering. We use Python and the standard scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.). Working closely with our product and analytics functions to ensure the product we deliver aligns closely with user needs and provides value to the wider Modo … team. Qualifications: 3 to 5 years experience using Python (or another programming language e.g. R, C++, Java) and with the scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.). Strong quantitative skills and a proven track record of solving complex technical problems using data analysis, machine learning, and optimization techniques. Hands-on experience with cloud environments (e.g., AWS) for deploying More ❯

our growing forecast offering. Developing our power market and dispatch models to grow and enhance Modo's product offering. We use Python and the standard scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.). Working closely with our product and analytics functions to ensure the product we deliver aligns closely with user needs and provides value to the wider Modo … team. Qualifications: 3 to 5 years experience using Python (or another programming language e.g. R, C++, Java) and with the scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.). A degree in a quantitative field such as mathematics, engineering, computer science, physics or a related discipline. Previous experience in energy modelling, with a specific focus on the GB and/ More ❯

our growing forecast offering. Developing our power market and dispatch models to grow and enhance Modo's product offering. We use Python and the standard scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.). Working closely with our product and analytics functions to ensure the product we deliver aligns closely with user needs and provides value to the wider Modo … team. Qualifications: 3 to 5 years experience using Python (or another programming language e.g. R, C++, Java) and with the scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.). A degree in a quantitative field such as mathematics, engineering, computer science, physics or a related discipline. Previous experience in energy modelling, with a specific focus on the GB and/ More ❯

discipline Understanding of NLP algorithms and techniques and/or experience with Large Language Models (fine tuning, RAG, agents) Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.) Have experience productionising machine learning models Are an expert in one of predictive modeling, classification, regression, optimisation or recommendation systems Have experience with Spark Have knowledge … information systems (GIS) Experience with cloud infrastructure Experience with graph technology and/or algorithms Our technology stack Python and associated ML/DS libraries (Scikit-learn, Numpy, LightlGBM, Pandas, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow More information: Enjoy fantastic perks like private healthcare & dental insurance, a generous More ❯

Snowflake, AWS, and Python Work directly with investment professionals to scope and deliver solutions What we’re looking for: Strong Python engineering skills, including use of data libraries like pandas and NumPy Experience working in front office environments Familiarity with data pipelines and cloud infrastructure Pragmatic, detail-oriented, and able to work independently Experienced Python-focused Software/Data Engineer More ❯

Snowflake, AWS, and Python Work directly with investment professionals to scope and deliver solutions What we’re looking for: Strong Python engineering skills, including use of data libraries like pandas and NumPy Experience working in front office environments Familiarity with data pipelines and cloud infrastructure Pragmatic, detail-oriented, and able to work independently Experienced Python-focused Software/Data Engineer More ❯

and iterate on solutions. Requirements 1-4 years of experience in a quantitative, analytics, or developer role within a financial institution or trading environment. Strong proficiency in Python (e.g., Pandas, NumPy, Jupyter) and experience building data pipelines , analytical tools , or dashboards . SQL experience is a plus. Proficiency in Excel and data visualization platforms such as Power BI, Tableau, or More ❯

and iterate on solutions. Requirements 1-4 years of experience in a quantitative, analytics, or developer role within a financial institution or trading environment. Strong proficiency in Python (e.g., Pandas, NumPy, Jupyter) and experience building data pipelines , analytical tools , or dashboards . SQL experience is a plus. Proficiency in Excel and data visualization platforms such as Power BI, Tableau, or More ❯

Frameworks : Scikit-learn, XGBoost, LightGBM, StatsModels PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working More ❯

Frameworks : Scikit-learn, XGBoost, LightGBM, StatsModels PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working More ❯

functional teams to analyze requirements and architect high-quality software solutions. Develop IT solutions using Python and related libraries for AI applications. Build scalable data pipelines utilizing technologies like Pandas, NumPy, or Spark. Apply Agile and DevOps practices to deliver effective solutions. Understand and translate business requirements into technical specifications. Identify opportunities for enhancing DevOps processes and explore new technologies. More ❯

to detail, and clear communication skills Nice To Have: Prior exposure with execution algos, TCA, order-routing, or market-impact modelling Knowledge of statistical or machine-learning libraries (NumPy, pandas, scikit-learn, PyTorch) Experience building distributed systems with message buses (Kafka, ZeroMQ) and asynchronous I/O Experience with cloud or on-prem orchestration and scheduling frameworks (Kubernetes, HT Condor More ❯

or mentorship. Have good communication skills. Nice to have Experience deploying LLMs and agent-based systems Our technology stack Python and associated ML/DS libraries (scikit-learn, numpy, pandas, LightGBM, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, ECR, Athena, etc. MLOps: Terraform, Docker, Spacelift, Airflow, MLFlow Monitoring: New Relic CI/CD: Jenkins, Github Actions More ❯

in a healthcare/life science organization is considered an asset. Other skills we are searching for are: Programming Skills: Proficiency in Python, data analytics, deep learning (Scikit-learn, Pandas, PyTorch, Jupyter, pipelines), and practical knowledge of data tools like Databricks, Ray, Vector Databases, Kubernetes, and workflow scheduling tools such as Apache Airflow, Dagster, and Astronomer. GPU Computing: Familiarity with More ❯

future. We expect this team to work across multiple technologies around a core, includingPython, AWS (EKS, S3, Lambda, CDK, etc.), AI/ML/Data Science libraries (LLM tooling, pandas, etc.) About Role: We are hiring several Software Engineers of differing levels to build AI capabilities through the delivery of AI-powered features within PatentSight+ and internal AI tools. PatentSight+ More ❯

Proficiency in one of the programming language - R or Python Working knowledge of key R libraries like tidyverse and ggplot2 (if proficient in R) or key Python libraries like Pandas, Numpy and Matplotlib (if proficient in Python) Familiarity with R-Markdown(if proficient in R) or Jupyter notebook (if proficient in Python) Working knowledge of SQL to query databases Advanced More ❯

functional teams to enhance testing practices across cloud-native microservices and data platforms. You'll develop scalable test automation frameworks with a focus on data validation using tools like Pandas, and lead strategies for testing data lakes. Collaborate closely with QA and Java/Spring Boot development teams to ensure data quality and reliability across our sports technology ecosystem. What … Your Day Will Look Like Build scalable and robust frameworks for validating complex data systems, pipelines, and APIs using tools like Pandas, Great Expectations, and Java modules. Collaborate with development teams to design and implement automated tests for microservices, emphasizing Spring Boot and Java-based architectures. Implement testing strategies for AWS data lakes (e.g., S3, Glue, Athena) with a focus … methodologies and train teams to independently implement and use the automation frameworks. Skills, Knowledge, and Expertise Expertise in validating complex datasets, creating synthetic test data, and leveraging tools like Pandas and Python for comprehensive data quality assurance. Proven ability to build and maintain scalable test automation frameworks, with a focus on backend, API, and data systems using tools like Pytest More ❯

functional teams to enhance testing practices across cloud-native microservices and data platforms. You'll develop scalable test automation frameworks with a focus on data validation using tools like Pandas, and lead strategies for testing data lakes. Collaborate closely with QA and Java/Spring Boot development teams to ensure data quality and reliability across our sports technology ecosystem. What … Your Day Will Look Like Build scalable and robust frameworks for validating complex data systems, pipelines, and APIs using tools like Pandas, Great Expectations, and Java modules. Collaborate with development teams to design and implement automated tests for microservices, emphasizing Spring Boot and Java-based architectures. Implement testing strategies for AWS data lakes (e.g., S3, Glue, Athena) with a focus … methodologies and train teams to independently implement and use the automation frameworks. Skills, Knowledge, and Expertise Expertise in validating complex datasets, creating synthetic test data, and leveraging tools like Pandas and Python for comprehensive data quality assurance. Proven ability to build and maintain scalable test automation frameworks, with a focus on backend, API, and data systems using tools like Pytest More ❯

Building from the beginning – lots of IT Challenges – Python Code Migrating from library, tweaking, methodology. Skills: Quant Developer Python: Blackrock numeric data processing: numpy, scipy text data processing: pyarrow, pandas databases: sqlalchemy, psycopg parallelization: multiprocessing, concurrent.futures More ❯

Building from the beginning – lots of IT Challenges – Python Code Migrating from library, tweaking, methodology. Skills: Quant Developer Python: Blackrock numeric data processing: numpy, scipy text data processing: pyarrow, pandas databases: sqlalchemy, psycopg parallelization: multiprocessing, concurrent.futures More ❯

Building from the beginning – lots of IT Challenges – Python Code Migrating from library, tweaking, methodology. Skills: Quant Developer Python: Blackrock numeric data processing: numpy, scipy text data processing: pyarrow, pandas databases: sqlalchemy, psycopg parallelization: multiprocessing, concurrent.futures More ❯

experience of Bedrock, Sagemaker, Python and Pandas. Key Responsibilities: * Working experience LLMs under Bedrock and Sagemaker both Amazon * Python with APIs to ChatGPT * Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Key Skills & Experience: AWS Data Science Environment: Hands-on experience with Sage Maker, Lambda, Step Functions, S3, Athena. Model deployment and pipeline … OCR Use-Case Development: Proficiency with Amazon Tex-tract, Tesseract, and LLM-based OCR. Building document parsing pipelines, validations, and rule Python Proficiency: Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Writing clean, modular, and testable code. Traditional Machine Learning Models: Experience with regression (linear, ridge), classification (logistic regression, decision trees, random forests More ❯