Data Science Training Expert

2 months ago

Cheltenham, Gloucestershire, United Kingdom QA Full time
Job Description

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

Job Summary:

We are seeking an experienced Technical Trainer with a strong background in practical data science to join our team at QA. 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.
Tools and Technologies:
  • Visual Studio
  • Jupyter Notebooks
  • Git
  • Gitlabs
  • Docker
  • Kebernates
  • Apache Spark
  • MatLab
  • TensorFlow

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