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.
- 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.
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.