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Part-Time Data Science Mentor (Us)
Company | Interview Kickstart |
Address | United States |
Employment type | PART_TIME |
Salary | |
Category | Software Development,Technology, Information and Internet,Computer Games |
Expires | 2023-08-30 |
Posted at | 9 months ago |
Who are we, you ask?
Interviews can be hard. And when it comes to the top tech companies like Google, Facebook, Netflix, etc., they can be downright brutal. Most candidates don’t make it simply because they don’t prepare well enough. IK helps candidates nail the toughest tech interviews. At IK, current and former hiring managers at these top companies take candidates through an intense prep course to make them completely ready to crack the toughest interviews. You could think of us as “the everything store” for career transitions and interview skill development.
We are looking for Data Scientists, with a strong passion for teaching to join us as part-time instructors to teach data science concepts. This role will provide opportunities to network with other experts, understand learner issues and contribute to the engineering community at large.
Responsibilities:
- Simplify complex topics and explain them in an engaging manner
- Deliver live sessions on various topics that are relevant for Data Science interviews
- Understand the challenges faced by students and willingness to help them out
- Have regular discussions with IK’s curriculum team in evolving the Data Science curriculum
- Constantly improve the session flow and delivery by working with other instructors and subject matter experts
- Help in onboarding and training other instructors and coaches
Requirements:
- Minimum 4 years of experience in tier-1 Tech companies as a Data Science Engineer/ Data Scientist/ ML Engineer/ Decision Scientist
- Experience in delivering end-to-end solutions related to Data Science Projects
- Proficient in SQL and at least one of these programming languages: Python (preferred), R, C/C++
- Participation in interview panels and hiring committees
- Should be willing to work on weekends/evenings and be available as per the US time zone
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