Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Jupyter Notebooks Consultant

N Consulting Ltd
London
10 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Portfolio Data Analyst

Machine Learning Researcher

2026 Data Science Analyst - Full Time Analyst - Glasgow & London

Senior Product Manager - Machine Learning and AI

Data Science Principal


Job Title: Jupyter Notebooks
Location: London
Work model: Hybrid

Key Responsibilities
Develop and maintain reproducible data analysis workflows and visualizations in Jupyter Notebooks.
Utilize libraries such as Pandas, NumPy, Matplotlib, Seaborn, and Plotly for data manipulation and visualization.
Collaborate with cross-functional teams to extract, clean, and analyze data for business insights.
Build and train machine learning models using frameworks like scikit-learn, TensorFlow, or PyTorch.
Integrate data from multiple sources (e.g., databases, APIs, flat files) and ensure consistency across notebooks.
Use Jupyter Notebooks for creating dynamic reports and interactive dashboards (e.g., with Voila, Jupyter Dashboards, or Bokeh).
Debug and optimize Jupyter Notebook workflows for performance and scalability.
Document and version-control notebooks using Git or similar tools.
Stay current with emerging data science tools and best practices to enhance productivity.

Required Skills and Qualifications
Proficiency in Python programming and familiarity with Jupyter Notebook extensions.
Hands-on experience with data analysis libraries (e.g., Pandas, NumPy) and visualization tools (e.g., Matplotlib, Seaborn, Plotly).
Strong understanding of data science methodologies, statistics, and machine learning algorithms.
Experience with relational databases (e.g., SQL, PostgreSQL) and data querying.
Familiarity with version control tools like Git and cloud platforms (e.g., AWS, Google Cloud, or Azure).
Strong communication skills for presenting findings in a clear, reproducible manner.
Ability to debug and troubleshoot issues within Jupyter Notebooks and related code.

Preferred Qualifications
Experience with interactive dashboards using Voila, Streamlit, or Dash.
Familiarity with notebook infrastructure tools like JupyterHub, Binder, or Kubernetes for Notebooks.
Knowledge of big data tools and frameworks (e.g., Spark, Dask).
Background in scientific computing, such as SciPy or SymPy.
Experience in integrating Jupyter Notebooks with CI/CD pipelines for data workflows.
Certifications in Data Science, Machine Learning, or related fields.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Jobs

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Jobs

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.