1 to 25 of 33 Remote Permanent Jupyter Jobs

areas: Big Data Analytics (e.g. 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 ideal but not essential A More ❯

management readiness. Proven track record 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 independently and take ownership of More ❯

and interpreting large datasets. Ability 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 package, on a standard vesting More ❯

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 GPU computing More ❯

Query Language (NoSQL), Application Program Interface (API) Building, Extract, Transform, and Load (ETL) pipelines, Web Application Servers, or Search Index. Experience using programming languages and products such as Python, Jupyter Notebook, Pandas, Numpy, Requests, or Antigravity. Experience applying complex mathematical and statistical concepts. Experience applying statistical and operations research methods and tools. Experience employing spreadsheets for data manipulation and visualization. More ❯

your data science expertise and the Orise Digital AI algorithms to real-world industrial or IoT data: pre-processing, cleaning, training, and evaluating anomaly detection and predictive models in Jupyter notebooks or in the UI of Orise Digital AI. Communicating results to clients, gathering their feedback, and refining your work accordingly. Enhancing algorithms in our scalable big-data platform for … . Tuning algorithms and data pipelines for optimal performance when required. Your profile You tick the following boxes: Proficiency in Python and its data science stack (pandas, scikit-learn, Jupyter, Luigi, etc.). Strong knowledge of data mining and machine learning. Experience with optimization algorithms is a plus. A passion for writing clean, maintainable, and robust code. A Bachelor's More ❯

machines). • Experience working with 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 Join MITRE? Why choose between More ❯

programming languages such as Python. Agile development experience along with related technologies (e.g., Jira). Ability, openness, and eagerness to learn. Skills: Data Analytics Data Science Data Visualization GitLab Jupyter Notebooks Python and R Studio Full-Time Employee Compensation M9 Solutions' pay range for this position is a general guideline only and not a guarantee of compensation or salary. Additional More ❯

Playwright or similar testing frameworks. 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 management libraries (MobX, Redux). More ❯

high-performance data platforms Experience 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 Compose Why join us? Shape More ❯

React or similar frameworks. Provide 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, transform and load (ETL); and More ❯

Knowledge of common data science 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 and grow A positive, collaborative More ❯

the-art research areas (e.g., NLP, Transfer Learning, etc.), and modern Deep Learning algorithms (e.g., BERT, LSTM, etc.) Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib, etc.) Understanding of model evaluation, data pre-processing techniques, such as standardisation, normalisation, and handling missing data Solid understanding of summary, robust, and nonparametric statistics; hypothesis More ❯

Strong background in math and/or algorithm development • Strong Python programming experience • Experience with common software development and management tools such as Git, Nexus, JIRA, Confluence, VSCode and Jupyter • DevSecOps experience including CI/CD pipelines to build, test, and deploy • Effective oral and written communication skills Desired Skills: Desired Skills: Additional skills in the following areas are desired More ❯

and other Qualtrics products Acquire data from customers (usually sftp or cloud storage APIs) Validate data with exceptional detail orientation (including audio data) Perform data transformations (using Python and Jupyter Notebooks) Load the data via APIs or pre-built Discover connectors Advise our Sales Engineers and customers as needed on the data, integrations, architecture, best practices, etc. Build new AWS More ❯

include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series More ❯

include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series More ❯

include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series More ❯

include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series More ❯

DevOps Methodologies: experience of working on Agile projects Good understanding of SOA/Microservices based architectures Good understanding of OOP, SOLID principles and software design patterns Knowledge of Python (Jupyter notebooks) Benefits offered Bonus, Pension (9% non-contributory plus additional matched contributions), 4 x Life Assurance, Group Income Protection, Season Ticket Loan, GAYE, BUPA Private Medical, Private GP, Travel Insurance More ❯

Big Data solutions (ecosystems) and technologies such as: Apache Spark and the Hadoop Ecosystem Excellent knowledge of YAML or similar languages The following Technical Skills & Experience would be desirable: Jupyter Hub Awareness RabbitMQ or other common queue technology e.g. ActiveMQ NiFi Rego Familiarity with code development, shell-scripting in Python, Bash etc. To apply for this DV Cleared DevOps Engineer More ❯

Technical experience with cyber data analysis to include continuous monitoring, intelligence, and reporting. Proficient in various query languages (SQL, KQL (Kusto). Python experience, and bonus for experience using Jupyter notebooks. Experience with dashboarding/visualizations (Power-Bi, Superset, Kibana). Ability to abstract threat hunting concepts to look at the 'big picture' and discover threats that aren't captured More ❯

and Experience required Extensive background in delivering production-grade, data-centric applications for quantitative trading and analytics, with demonstrated expertise in: The python data engineering stack (Polars, Parquet, FastAPI, Jupyter, Airflow, Streamlit, Ray) High-performance data stores and query engines (Starburst, Snowflake) Real-time streaming analytics technologies (Kafka, Flink) Cloud container technologies (AWS, Azure, GCP, Docker, Kubernetes) Proven success in More ❯

building machine learning models for marketing use cases ADVANCED skills in segmentation, recommendation, campaign optimisation, forecasting, etc. Proficiency in Python, SQL, Bash, and Git. Familiarity with tools like Pandas, Jupyter notebooks, PyTorch. Experience with advanced techniques including CausalAI, NLP, RNNs, GraphAI, GenAI, and Computer Vision. Solid understanding of experimentation methods including A/B testing. Strong communication skills and ability More ❯

business stakeholders to understand business requirements and develop solutions that meet those requirements. Writing clean and efficient code, and implementing best practices for code optimization, testing, and deployment through Jupyter Notebooks and/or Google Colab. Conducting research and staying up-to-date with the latest AI and Machine Learning techniques, and incorporating new ideas and methods into existing systems. More ❯