About the Job
This is a role that will enable you to utilize your Data Science expertise to make a positive impact on individuals. You'll be instrumental in shaping the learning experience of our students, providing them with valuable insights and skills that will enhance their careers.
As a Data Science professional, you'll have the opportunity to teach others, share your knowledge, and contribute to the growth and development of our students.
Responsibilities:
* Develop and deliver online lectures that are engaging and interactive, incorporating real-world examples and case studies to illustrate key concepts.
* Design and facilitate group projects that promote collaboration, critical thinking, and problem-solving skills among students.
* Provide individualized support and feedback to students, helping them to overcome challenges and achieve their goals.
* Create a positive and inclusive learning environment that fosters a sense of community and belonging among students.
* Mentor and guide students in the application of theoretical concepts to practical problems, promoting hands-on learning and experiential education.
Required Skills & Qualifications:
* Bachelor's degree in a relevant field (e.g., Computer Science, Mathematics, Statistics)
* A minimum of 5 years of work experience in Data Science or a related field
* Strong communication and interpersonal skills, with the ability to engage and motivate students from diverse backgrounds
* Proficiency in statistical programming languages (e.g., R, Python) and data visualization tools (e.g., Tableau, Power BI)
* Familiarity with machine learning algorithms and techniques, including supervised and unsupervised learning methods
Benefits:
* Ongoing professional development opportunities, including training and mentorship programs
* Collaborative and dynamic work environment that encourages innovation and creativity
* Competitive compensation package, including benefits and perks
* Opportunities for career advancement and leadership development
Logistics:
* 24-week program with part-time commitment
* Class schedule: Monday, Tuesday, Thursday
* Class times: 6:00 pm - 10:15 pm (includes office hours and breaks)