1 to 25 of 77 Remote Jupyter Jobs

Google BigQuery/BigTable, Apache Spark), Parallel Computing (e.g. Apache Spark, Kubernetes, Databricks), Cloud Engineering (AWS, GCP, Azure), Spatial Query Optimisation, Data Storytelling with (Jupyter) Notebooks, Graph Computing, Microservices Architectures Modelling & Statistical Analysis experience, ideally customer related A university degree - numbers based, Computer Science or Geography Relevant industry sector knowledge More ❯

to take research from concept to business impact. Strong Python toolkit proficiency for Data Science, with experience in SQL and NoSQL databases. Familiarity with Jupyter Notebooks and Git version control. Expertise in working with large, sophisticated datasets and extracting actionable insights. Project management experience with tight deadlines. Ability to work More ❯

to take research from concept to business impact. Strong Python toolkit proficiency for Data Science, with experience in SQL and NoSQL databases. Familiarity with Jupyter Notebooks and Git version control. Expertise in working with large, sophisticated datasets and extracting actionable insights. Project management experience with tight deadlines. Ability to work More ❯

to take research from concept to business impact. Strong Python toolkit proficiency for Data Science, with experience in SQL and NoSQL databases. Familiarity with Jupyter Notebooks and Git version control. Expertise in working with large, sophisticated datasets and extracting actionable insights. Project management experience with tight deadlines. Ability to work More ❯

to take research from concept to business impact. Strong Python toolkit proficiency for Data Science, with experience in SQL and NoSQL databases. Familiarity with Jupyter Notebooks and Git version control. Expertise in working with large, sophisticated datasets and extracting actionable insights. Project management experience with tight deadlines. Ability to work More ❯

engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). Experience with cloud services More ❯

engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). Experience with cloud services More ❯

to apply statistical techniques to validate models and algorithms. Data Manipulation & Analysis: Proficient in data manipulation and analysis using tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau to communicate insights effectively. Our offer: Cash: Depends on experience Equity : Generous equity More ❯

are: style="margin-bottom:0.0in;margin-top:0.0px;text-align:justify"- -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 More ❯

evaluate, analyze and interpret model results resulting in further improvement of existing statistical model performance You can perform complex data analysis using SQL/Jupyter notebook to find underlying issues and propose a solution to stakeholders explaining the various trade-offs associated with the solution. You can use your grit More ❯

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 More ❯

for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. Master's degree More ❯

for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. Master's degree More ❯

for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. Master's degree More ❯

for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. Master's degree More ❯

of Generative LLM's • Fundamental knowledge of ML, and basic knowledge of AI, NLP, and Large Language Models (LLM) • Comfortable working with Python and Jupyter Notebooks • Should have in-depth knowledge and familiarity with cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Technical Skills More ❯

databases (e.g., PostgreSQL, Oracle, MySQL, MongoDB, Neo4J). • Experience using version control (e.g., Git, Mercurial, SVN) to support collaborative development. • Experience utilizing notebooks (e.g., Jupyter, R Markdown, Zeppelin). • Experience developing interactive data visualizations using open-source technologies (e.g., Angular, Vue, React, D3.js) or other frameworks (e.g., Shiny). Why More ❯

science, data analytics or any subjects with a strong focus on analytics You must be excellent with analytical tools and languages such as SQL, Jupyter, Python or R Familiarity with data visualisation tools (e.g., Power BI, Tableau). At Cooper Parry we are mindful of candidates who may have extenuating More ❯

REST APIs: Strong understanding of integrating and working with RESTful services. Data Skills: Experience in data wrangling/analysis (e.g., using SQL or Python, Jupyter Notebook). Collaboration: Experience working in an Agile environment (Scrum/Kanban). Problem-Solving: Strong analytical and troubleshooting skills. Desirable Skills Familiarity with state More ❯

with data engineering Our current tech stack: Frontend Technologies - React, Material UI Backend & Application Frameworks - Go, Node, RabbitMQ Databases - Postgres, MariaDB, MongoDB, ClickHouse, Redis, JupyterLab, Metabase Data Engineering & Orchestration - Python, Airflow, Kafka, DataHub Cloud & Infrastructure - AWS, K8s DevOps & CI/CD - Git, GitLab CI, DBS, Grafana, ELK, Prometheus, Docker, Docker More ❯

with complex event processing and real-time streaming data 3 Years Experience with deployment and management of data science tools and modules such as JupyterHub 3 Years Experience with ETL, data processing, analytics using languages such as Python, Java or R 3 Years Databricks Certified Data Engineer Professional - Highly desired More ❯

guidance to less experienced front-end engineers. • General knowledge of machine learning and reinforcement learning concepts, frameworks, and environments, such as Pandas, TensorFlow, and Jupyter Notebook. • Broad knowledge of the general features, capabilities, and trade-offs of common data warehouse (e.g. Apache Hadoop); workflow orchestration (e.g. Apache Beam); data extract More ❯

in Data Management, Biostatistics, and Centralized Monitoring At least 2 years of experience in SAS and at least one of the following: R, Python, Jupyter, SQL, Shiny, Spark and associated packages and libraries Full professional proficiency in English Strong analytical and logical thinking Communication and collaboration skills Nice to have More ❯

software. We have a Python-first setup, but will if needed tackle problems using R, SAS, SQL, Spark, and work with tools such as Jupyter Notebooks, IDE's, Git, Microsoft Azure, Obviously, additional bonus points for PhD's, and more specific knowledge like e.g. Keras, D3.js The desire to learn More ❯

statistics and probability skills, with a strong level of ability to structure, analyse and interpret data Competent with SQL and Python, and use of Jupyter Notebook environment (or similar) Strong understanding of machine learning techniques such as time series modelling, regression, classification, clustering and anomaly detection Capable of explaining data More ❯