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