76 to 100 of 144 Permanent Jupyter Jobs

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 ❯

preprocessing, model development and evaluation, and software integration Experience in software engineering in industry Experience bringing machine learning-based products from research to production Experience with scientific communication tools (Jupyter, Matplotlib) Research and software engineer experience demonstrated via an internship, contributions to open source, work experience, or coding competition Public Compensation: $56.25/hour to $173,000/year + 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 ❯

. Data Engineering: Proficiency in data preprocessing and feature engineering. Version Control: Experience with GitHub for version control. Development Tools: Proficiency with development tools such as VS Code and Jupyter Notebook. Containerization: Experience with Docker containerization and deployment techniques. Data Warehousing: Knowledge of Snowflake and Oracle is a plus. APIs: Familiarity with AWS Bedrock API and/or other GenAI More ❯

effectively and confidently Build great relationships with Data Science, Technology, Finance, Collections, Ops and other stakeholders What you'll need Excellent SQL skills Python data science stack (pandas, NumPy, Jupyter notebooks, Plotly/matplotlib, etc) A drive to solve problems using data Experience in a management role What would be a bonus: Familiarity with Git Data visualization tool (Tableau, Looker 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 ❯

and evaluate highly innovative models for Natural Language Programming (NLP), Large Language Model (LLM), or Large Computer Vision Models. Use SQL to query and analyze the data. Use Python, Jupyter notebook, and Pytorch to train/test/deploy ML models. Use machine learning and analytical techniques to create scalable solutions for business problems. Research and implement novel machine learning 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 ❯

This is a new position for a Data Scientist with a global, data-driven company with cutting-edge technology who leverage data to serve as a true market differentiator. The focus of this role is to deliver data science solutions More ❯

This is a new position for a Data Scientist with a global, data-driven company with cutting-edge technology who leverage data to serve as a true market differentiator. The focus of this role is to deliver data science solutions 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 ❯

to generate analytics that enhance client service, partnering with traders, salespeople, and strategists across asset classes to promote platform adoption and deliver relevant, timely content. Key technologies include Python, Jupyter, Pandas, Trino, and SQL. RESPONSIBILITIES AND QUALIFICATIONS: Design and implement programmatic solutions to meet client needs Proficient in scripting languages such as Python Knowledge of data science and machine learning More ❯

service. You will work closely with Traders, Salespeople, and Strats across asset classes to produce insights that promote platform adoption and deliver relevant, timely content. Technologies used include Python, Jupyter, Pandas, Trino, and SQL. RESPONSIBILITIES AND QUALIFICATIONS Passion for designing and implementing programmatic solutions to client needs Excellent programming skills in languages like Python Knowledge and experience in data science More ❯

a more effective platform; Open to traveling to Octopus offices across Europe and the US. Our Data Stack: SQL-based pipelines built with dbt on Databricks Analysis via Python Jupyter notebooks Pyspark in Databricks workflows for heavy lifting Streamlit and Python for dashboarding Airflow DAGs with Python for ETL running on Kubernetes and Docker Django for custom app/database More ❯

large-scale analytics platform. Proficiency in Python or R, including libraries like Pandas. Experience working with BI tools such as Looker, Tableau, Power BI, or Mode. Confidence working in Jupyter or similar notebook environments. A solid grasp of ETL processes and associated best practices. Familiarity with Git, Agile workflows, and DevOps tooling is advantageous. Exposure to customer/product analytics 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 ❯

the tools work and how we can use software development to fulfil engineering project requirements efficiently What technology do we use? JavaScript, Vue, Observable, Nuxt, TypeScript, Tailwind Python, FastAPI, Jupyter, JupyterHub, Voila SQL Git, GitHub Ansible Revit, Revit API, pyRevit IES, IES Python API Rhino, Grasshopper and the supporting ecosystem ABOUT YOU We value people who can think analytically and More ❯

services. The CCE provides several containerized services that customers can provision and access on demand inside of a Kubernetes cluster. Some of the services include Gitlab CI/CD, Jupyter Notebooks, MinIO, and several other products. The Software Engineer shall perform maintenance and troubleshooting of containerized applications, upgrade services, assist customers using the CCE and develop any required software for … Charts for Kubernetes Experience with developing services on Kubernetes. Experience creating containerized applications/services using Docker. Experience providing customer outreach and troubleshooting support. Position Desired Skills Experience with Jupyter Notebooks Experience with Gitlab CI/CD pipelines Experience updating containerized applications to address STE/STN requirements Experience developing with REST APIs Experience with the Atlassian Tool suite (Bitbucket More ❯

related or quantitative discipline, you will have insurance P&C experience. You will also be proficient in various coding languages (e.g. R, Python) and development environments (e.g. R Studio, Jupyter, VS Code). Alongside this, you will be experienced in data visualization and communication around this to present insights to a non-technical audience. In this key role, you will More ❯

Strong problem-solving and analytical skills Experience in support roles, incident triage, and handling (SLAs) Linux system administration basics, Bash scripting, environment variables Experience with browser-based IDEs like Jupyter Notebooks Familiarity with Agile methodologies (SAFE, Scrum, JIRA) Languages and Frameworks: JSON YAML Python (advanced proficiency, Pydantic bonus) SQL PySpark Delta Lake Bash Git Markdown Scala (bonus) Azure SQL Server More ❯

logical data models Experience with enterprise scale relational databases Experience with building queries in SAP HANA studio using BW/4HANA Objects. Experience with reporting tools - Microsoft PowerBI, Tableau, Jupyter Notebooks Experience with developing SAP S4/HANA CDS Views. Experience with large data volume, performance tuning Experience in ABAP programming skills and SQL Skills. Experience with SDLC methodologies: Agile More ❯

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 Plotly/ More ❯