Data Science
(Machine Learning) Instructor
About the job
As a Data Science Instructor at Brainster, you can make a significant impact by training and mentoring the next generation of professionals. Your role will involve creating a supportive and engaging learning environment and serving as a role model for students.
By delivering lessons from the curriculum, through mentoring and sharing practical knowledge, serving as a subject matter expert, you will guide the students through intricacies of Machine Learning, nurture their understanding of machine learning techniques, and empower them to creatively solve real-world problems with newfound expertise. Through your guidance, students will delve into supervised and unsupervised algorithms, deep neural networks, computer vision, and Natural Language Processing, while fostering practical problem-solving skills that bridge theory and real-world applications.
This is a part-time, hybrid position as all lectures at Brainster are conducted online and in real-time. Lectures are scheduled on weekday evenings and one workshop during the weekends, offering full-time employed professionals an excellent opportunity for a challenging additional job without disturbing their usual workday. The expected weekly commitment for this part-time role throughout the module is 10 hours.
Responsibilities:
- Create a Positive Learning Environment: Cultivate a welcoming and motivating atmosphere for learners, promoting engagement and knowledge retention through rapport building and open communication.
- Adapt Teaching Methods to Learner Needs: Tailor teaching methods and materials to diverse learning styles and backgrounds, ensuring effective comprehension and application of knowledge for all individuals.
- Facilitate Critical Thinking: Encourage critical thinking and problem-solving skills by using thought-provoking questions, interactive activities, and real-world case studies to inspire practical application of concepts.
- Inspire Motivation and Engagement: Infuse enthusiasm and energy into teaching, creating an enjoyable learning process that encourages active participation, effective information retention, and practical application.
- Effective Classroom Management: Maintain an organized learning environment by setting clear expectations, managing time efficiently, and handling disruptions to enable focused content absorption.
- Continuously Assess and Improve: Continuously gauge learners’ progress, adapt teaching strategies, and provide timely feedback using diverse assessment methods, reflecting on teaching practices to enhance effectiveness.
- Collaborate and Work as a Team: Actively collaborate with educators, trainers, and subject matter experts, contributing strong interpersonal skills to develop comprehensive training programs and improve overall instruction quality
- Demonstrate Measurable Impact: Contribute to organizational success by ensuring learners acquire job-relevant knowledge and skills, leading to enhanced job performance, increased productivity, and improved employee satisfaction, thereby quantifying our influence.
Requirements:
To be considered an ideal candidate for this role, you should possess the following qualifications:
- A minimum of 4+ years of professional experience in Data Science with a focus on Machine Learning
- Practical experience in working with various neural network architectures, including CNN, RNN, and LSTM
- Knowledge of algorithms like Naive Bayes, Decision Trees, SVM, and ensemble methods such as Random Forest and Gradient Boosting
- Experience with clustering methods like KMeans, Agglomerative Clustering, and dimensionality reduction techniques like PCA and tSNE
- Understanding of NLP tools and computer vision concepts for object recognition, identification, and classification
- Proficiency in implementing and explaining algorithms for supervised learning and unsupervised learning scenarios
- Curriculum development and lesson planning skills
- Previous experience as a mentor/instructor will be considered as an advantage.
Join our dynamic team and contribute to revolutionizing the EdTech industry.
