Senior learning Specialist - Data Science

QA
Cheltenham
10 months ago
Applications closed

Related Jobs

View all jobs

Senior ML Engineer

QC Specialist Data Analytics

Experienced Life Science Recruiter (Relocate to Boston, US)

Space Sector Roles

Lead Software Developer (Polygot - ASP.Net, C#, Java, Spring)

Internal Auditor - Public Sector Services

Role: Technical Trainer - Data Science

Location: Commutable London/Gloucester daily

Working environment: In-person Training, travel is required

Contract: Full time, 37.5 hrs per week

Package: competitive + benefits

Role Description:

Are you an experienced Technical Trainer with a strong background in practical data science, and ideally experience of teaching programming languages including Python and C.

You will be passionate about education, possess excellent communication skills, and have a proven track record of success. As a Technical Trainer, you will play a crucial role in empowering our learners with the skills and knowledge needed to excel in the rapidly evolving field of data science

Key Responsibilities: 

Instruction and Delivery: 

Conduct engaging and hands-on training sessions, workshops, and seminars for both non-data scientists and experienced data scientists. Deliver training content effectively, ensuring that participants gain practical skills and knowledge applicable to their roles. 

Curriculum Development: 

Design and develop comprehensive training programs focused on practical data science, tailored to meet the needs of our learners. 

Technical Expertise: 

Demonstrate a deep understanding of data science principles, Python programming, and proficiency in C.  Share real-world examples and experiences from a software engineering environment to enhance the practical relevance of training content. 

Assessment and Feedback: 

Provide constructive feedback to participants, identifying areas for improvement and additional support. 


Collaboration: 

Work closely with cross-functional teams, including sales, and projects, to align training programs with customer goals. 


Continuous Learning: 

Stay abreast of industry trends, emerging technologies, and best practices to ensure training content remains current and relevant. 


Qualifications: 

Educated/Certified in Computer Science, Data Science, or a related field or equivalent industry experience. Proven experience as a Technical Trainer with a focus on data science, Python, and C.  Strong programming skills in Python and C, with a solid understanding of software engineering principles. 

Use of some of the following tools: 

Visual Studio  Jupyter Notebooks  Git  Gitlabs  Docker  Kebernates  Apache Spark  MatLab  TensorFlow 

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Careers

10 Ways AI Pros Stay Inspired: Boost Creativity with Side Projects, Hackathons & More

In the rapidly evolving world of Artificial Intelligence (AI), creativity and innovation are critical. AI professionals—whether data scientists, machine learning engineers, or research scientists—must constantly rejuvenate their thinking to solve complex challenges. But how exactly do these experts stay energised and creative in their work? The answer often lies in a combination of strategic habits, side projects, hackathons, Kaggle competitions, reading the latest research, and consciously stepping out of comfort zones. This article will explore why these activities are so valuable, as well as provide actionable tips for anyone looking to spark new ideas and enrich their AI career. Below, we’ll delve into tried-and-tested strategies that AI pros employ to drive innovation, foster creativity, and maintain an inspired outlook in an industry that can be both exhilarating and daunting. Whether you’re just starting your AI journey or you’re an experienced professional aiming to sharpen your skills, these insights will help you break out of ruts, discover fresh perspectives, and bring your boldest ideas to life.

Careers

Top 10 AI Career Myths Debunked: Key Facts for Aspiring Professionals

Artificial Intelligence (AI) is one of the most dynamic and rapidly growing sectors in technology today. The lure of AI-related roles continues to draw a diverse range of job seekers—from seasoned software engineers to recent graduates in fields such as mathematics, physics, or data science. Yet, despite AI’s growing prominence and accessibility, there remains a dizzying array of myths surrounding careers in this field. From ideas about requiring near-superhuman technical prowess to assumptions that machines themselves will replace these jobs, the stories we hear sometimes do more harm than good. In reality, the AI job market offers far more opportunities than the alarmist headlines and misconceptions might suggest. Here at ArtificialIntelligenceJobs.co.uk, we witness firsthand the myriad roles, backgrounds, and success stories that drive the industry forward. In this blog post, we aim to separate fact from fiction—taking the most pervasive myths about AI careers and debunking them with clear, evidence-based insights. Whether you are an established professional considering a career pivot into data science, or a student uncertain about whether AI is the right path, this article will help you gain a realistic perspective on what AI careers entail. Let’s uncover the truth behind the most common myths and discover the actual opportunities and realities you can expect in this vibrant sector.

Jobs

Global vs. Local: Comparing the UK AI Job Market to International Landscapes

How to navigate salaries, opportunities, and work culture in AI across the UK, the US, Europe, and Asia Artificial Intelligence (AI) has evolved from a niche field of research to an integral component of modern industries—powering everything from chatbots and driverless cars to sophisticated data analytics in finance and healthcare. The job market for AI professionals is consequently booming, with thousands of new positions posted each month worldwide. In this blog post, we will explore how the UK’s AI job market compares to that of the United States, Europe, and Asia, delving into differences in job demand, salaries, and workplace culture. Additionally, we will provide insights for candidates considering remote or international opportunities. Whether you are a freshly qualified graduate in data science, an experienced machine learning engineer, or a professional from a parallel domain looking to transition into AI, understanding the global vs. local landscape can help you make an informed decision about your career trajectory. As the demand for artificial intelligence skills grows—and borders become more porous with hybrid and remote work—the possibilities for ambitious job-seekers are expanding exponentially. This article will offer a comprehensive look at the various regional markets, exploring how the UK fares in comparison to other major AI hubs. We’ll also suggest factors to consider when choosing where in the world to work, whether physically or remotely. By the end, you’ll have a clearer picture of the AI employment landscape, and you’ll be better prepared to carve out your own path.

🍪 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.