13 of 13 Remote Jupyter Jobs

to strong results. Experienced in engaging with non-technical partners to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Knowledge of OO programming, software design, i.e., SOLID principles, and testing practices. Knowledge and working experience of AGILE methodologies. Proficient with SQL. Familiarity with More ❯

to strong results. Experienced in engaging with non-technical stakeholders to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. Knowledge of Langchain, huggingface and LLM More ❯

and the intel cycle. Familiarity and experience with the Department of Homeland Security (DHS). Ability, openness, and eagerness to learn. Skills: Data Analytics Data Science Data Visualization GitLab Jupyter Notebooks Python and R Studio Clearance: Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information. Compensation and Benefits More ❯

into scalable solutions. Essential Experience & Skills 5+ years' engineering experience, with at least 3 years in ML Ops, Data Engineering, or AI infrastructure. Strong Python engineering skills (Pandas, Numpy, Jupyter, FastAPI, SQLAlchemy). Expertise in AWS services (certification desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face Trainer, etc. More ❯

visualization technology and capabilities (i.e., Power BI, Tableau). Exposure to a variety of data products that will complement data preparation, algorithm models and visualization development (i.e., Panda Libraries, Jupyter Notebooks, Power BI, etc.). Intermediate technical and analytical abilities with programming skills in a language such as Python. Basic understanding of the techniques to collect, organize, blend, cleanse and More ❯

/SOAP) 3 Years Experience 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 Experience with Cloudera Data Platform More ❯

Python) Start-up/Scale-up Experience Strong cloud skills (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Experience in automating deployments and orchestrating cloud environments Nice to have: Python (Jupyter, PyTorch), monitoring tools (Prometheus, Grafana), cloud databases (RDS, Aurora, Spanner), CI/CD tools (CircleCI), and data visualisation experience. This is a unique opportunity to join a visionary team redefining More ❯

etc.), state-of-the-art areas (e.g. NLP, Transfer Learning) and modern Deep Learning algorithms (e.g. BERT, LSTM) 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 (standardisation, normalisation, handling missing data) Solid understanding of statistics; hypothesis testing, probability distributions, sampling techniques Private Health 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 ❯

retrieval methods. Knowledgeable in various synthetic data generation approaches, such as GANs, VAEs, or rule-based systems. Experience writing unit tests for ML models and associated components. Knowledgeable with Jupyter notebooks and Python development. Experience cleaning and preparing structured datasets for training and analysis. Experience creating basic features to enhance data utility for machine learning models. Knowledgeable in using predefined More ❯

pipelines to clean, transform, and enrich data from various sources. Ensure that pipelines are automated, scalable, and fault-tolerant to accommodate large volumes of data. Experience with Notebooks (e.g., Jupyter, Databricks) for data exploration, analysis, and reporting. Design and optimise data workflows to streamline key processing tasks, enhancing operational efficiency. API Integration & Data Ingestion: Integrate external and internal APIs to More ❯

technology across the business. Machine Learning Engineer, key skills: Significant experience working as a Data Scientist/Machine Learning Engineer Solid knowledge of SQLandPython's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib). GCP, VertexAI experience is desirable (developing GCP machine learning services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and More ❯

scripts and visualizations to explore and summarize biological experiment data. Apply statistical techniques (e.g. descriptive statistics, t-tests, ANOVA, regression) to help interpret experiments Create reproducible analysis workflows using Jupyter, Python, and associated libraries. Work with scientists to understand experimental goals and tailor analyses accordingly. Document analyses and communicate findings in a clear, concise manner. Collaborate with the data engineering … statistics: distributions, hypothesis testing, confidence intervals, regression. Experience working with structured datasets Ability to produce clear, well-commented code and visual outputs (e.g. plots, dashboards). Comfortable working in Jupyter Notebooks and collaborating with experimental teams. A degree (BSc or MSc) in a quantitative field such as Biology, Bioinformatics, Statistics, Data Science, or related discipline. There is an excellent salary More ❯