1 to 25 of 141 Permanent Jupyter Jobs

a related field. Proven experience in machine learning applications such as recommendation systems, segmentation, and marketing optimisation. Proficiency in Python, SQL, Bash, and Git, with hands-on experience in Jupyter notebooks, Pandas, and PyTorch. Familiarity with cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong problem-solving skills and a passion for driving measurable business impact. Knowledge More ❯

a related field. Proven experience in machine learning applications such as recommendation systems, segmentation, and marketing optimisation. Proficiency in Python, SQL, Bash, and Git, with hands-on experience in Jupyter notebooks, Pandas, and PyTorch. Familiarity with cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong problem-solving skills and a passion for driving measurable business impact. Knowledge More ❯

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 ❯

with 10 years, bachelor's with 8 years, master's with 6 years, or PhD with 4 years Proficiency in data science languages and tools (e.g., Python, R, SQL, Jupyter, Pandas, Scikit-learn) Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and big data platforms (e.g., Spark, Hadoop) Strong background in statistics, data modeling, and algorithm development Ability to explain More ❯

learning models Build AI systems using Large Language Models Build processes for extracting, cleaning and transforming data (SQL/Python) Ad-hoc data mining for insights using Python + Jupyter notebooks Present insights and predictions in live dashboards using Tableau/PowerBI Lead the presentation of findings to clients through written documentation, calls, and presentations Actively seek out new opportunities More ❯

learning models Build AI systems using Large Language Models Build processes for extracting, cleaning and transforming data (SQL/Python) Ad-hoc data mining for insights using Python + Jupyter notebooks Present insights and predictions in live dashboards using Tableau/PowerBI Lead the presentation of findings to clients through written documentation, calls and presentations Actively seek out new opportunities More ❯

visualization required - Strong understanding of AI/ML algorithms and techniques - Proficiency in scripting languages such as Python, Scala, SQL - Experience working within coding environments such as Databricks and Jupyter - Experience developing and deploying software solutions within cloud such as AWS or Azure - Ability to work collaboratively with stakeholders and in a team environment - Excellent communication and documentation skills. - Tableau More ❯

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 with cloud data warehouses (e.g., Snowflake, Databricks, Redshift, BigQuery) Familiarity with data pipelines and orchestration tools like More ❯

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 with cloud data warehouses (e.g., Snowflake, Databricks, Redshift, BigQuery) Familiarity with data pipelines and orchestration tools like More ❯

analysis, artificial intelligence, or software engineering with data analysis software (R, Python, SAS, MATLAB). Experience with Windows server management and Power BI Report Service. Proficiency with Python/Jupyter Notebooks, SQL and relational databases, ElasticSearch/Kibana. Background working with analyst teams including conducting data analysis and creating data visualizations. Experience with graph analytics, data pipelines, and IP-based 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 ❯

H14A/9326, H15A/9327, H16A/9328, H33A, H34A) Experience or familiarity with data analytics and/or the following advanced scripting languages and tools: Python, SQL Jupyter Pig ELK Stack Splunk PowerBI Jupyter Notebooks _ Compensation ranges encompass a total compensation package and are a general guideline only and not intended as a guaranteed and/or implied More ❯

field. Proven experience in machine learning applications such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science teams. Deep knowledge More ❯

field. Proven experience in machine learning applications such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science teams. Deep knowledge More ❯

field. Proven experience in machine learning applications such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science teams. Deep knowledge More ❯

improve our ability to serve clients. Tech Skills Required: Advanced level of coding in Python for Data Science Software engineering architecture design for application with integrated Data Science solutions Jupyter server/notebooks AWS: EC2, Sagemaker, S3 Git version control SQL skills include selecting, filtering, aggregating, and joining data using core clauses, use of CTEs, window functions, subqueries, and data More ❯

learning models Build AI systems using Large Language Models Build processes for extracting, cleaning and transforming data (SQL/Python) Ad-hoc data mining for insights using Python + Jupyter notebooks Actively seek out new opportunities to learn and develop Be an example of data science best-practice e.g. Git/Docker/cloud deployment Write proposals for exciting new More ❯

frameworks and tools such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, sci-kit-learn and PyTorch Experience with popular Python frameworks such as Django, Flask or Pyramid Experience with Jupyter Notebooks Experience with EDA and data visualization libraries such as Matplotlib, Seaborn, pygWalker, etc. Additional Technical Requirements: Advanced SQL skills Familiarity with Git version control Familiarity with containerization technologies (e.g. More ❯

with Remote Desktop Protocol (RDP) technologies Experience with data access control, specifically Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) Familiarity with data science platforms (Anaconda, Jupyter, NiFi) Experience with Python, C#, or similar languages will be beneficial Knowledge of modern web development frameworks (Node.js, React, Angular) Experience developing and maintaining complex systems that involves integrating open 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 ❯

preparation, data governance and analytic development and production Must have in-depth experience with at least two of the following advanced scripting languages and tools; Python, R, SQL, Lucene, Jupyter, Pig, Scala, ELK Stack, Splunk, PowerBI, or Jupyter Notebooks Compensation Range: $186,000 - $245,000 _ Compensation ranges encompass a total compensation package and are a general guideline only and not 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 ❯

Must be willing to achieve required skill certification promptly. Prefer current DoD IAT II or higher certification. Willingness to do a programming challenge during the interview process. Experience with Jupyter Notebooks, Python Data Science Libraries. Experience with ML-OPS and related tools (e.g., MLFLOW, Sagemaker, Bedrock) and ability to build interactive, insightful dashboards for monitoring ML models. Place of Performance More ❯