Data Science Career Discussion: The 2-Hour Job Search Method

Description for This Meeting

For this meeting, we'll be exploring Steve Dalton's job searching method as described in the book "The 2-Hour Job Search". We can then discuss

- What takeaways you have from the book
- Whether you agree / do not agree with specific points in the book
- In what ways do you find this method different from other methods
- Whether you find it useful for data science job search
- If you applied this method to your job search and how effective it was
- Etc.

The book's official page:
https://2hourjobsearch.com/

Please also read these articles before the meeting:

• https://www.linkedin.com/pulse/summary-steve-daltons-book-2-hour-job-search-philip-hoberg/
• https://blogs.darden.virginia.edu/careercorner/2021/03/18/the-2-hour-job-search-can-this-method-work-for-you/

Before this meeting starts, you're strongly recommend to search different job boards, articles, books, etc. related to the discussion topic. This will help you to participate in the discussions better.

Please also feel free to engage in discussions on our social media platforms (see group home page for more info).

We continue to strive to make this series useful for the community! Let us know how we can structure these meetings moving forward and bring the most value from continued participation.

Meetup Series Description
This is a series within the Learn Data Science group. Participants will discuss topics related to data science (DS) careers and help each other with advancing their own career in the field. This series may also involve other activities such as networking with people in data science, share thoughts and strategies on how people may plan their career, improve their skills and reach their career goals. People with different skills and experience levels are welcome.

Schedule
6:00PM to 8:00PM PST
Every 2 weeks on Tuesday

Meeting Venue
Online; see link after RSVP

Meeting Agenda
Prior to each meeting, a member is asked to set the meeting topic in advance. It could be based on a question you have about DS career, your personal experiences, an article / book / research paper you read recently, etc. Members are encouraged to research the topic beforehand to better discuss it.

During each meeting, the first 15 minutes are used for member mingling / networking, and the main activities will start afterwards. (Note: the mingling time has been changed from 30 min to 15 min based on participant feedback.) The host will ask the person who chose the topic to elaborate on what the topic is about. The host will then go around the room to ask each member to share their thoughts in turn. (It’s OK to pass your turn if you have nothing to say.) Members can jump in and discuss. At the end of each meeting, members can nominate and vote for the next meeting topic.

Example topics may include (but not limited to):

• What are current trends in the data science profession and job market?
• What kinds of DS jobs and career paths are out there? How does day-to-day work actually look like?
• What are effective strategies for searching jobs, getting interviews and getting hired?
• There are so many DS skills to learn. Which ones should I prioritize?
• How do I create a DS project that makes my skills stand out?
• How do I improve my coding skills?
• Etc.

Other activities involved during a meeting may include the following:

• Announce if you're seeking or hiring for a DS-related job.
• Announce if you're looking for mentors or offering mentorship.
• Personal project discussions: If you're working on a personal data science project, you can discuss their project with other members for feedback (e.g., getting a second opinion, solving bottlenecks, presenting results). It also helps to keep your project development stay on track.

Messaging Platforms

IMPORTANT NOTE: Starting from May 6, 2023, the Learn Data Science online chat group will migrate from Slack to Discord.

Discord: https://discord.gg/C5nK6wxY
GitHub: https://github.com/learn-data-science
For more details, refer to the Learn Data Science group info at https://www.meetup.com/learndatascience/

Group Policies

• Please keep discussions respectful and foster a welcoming environment. It helps everyone to learn and grow together!
• Individuals who maliciously disrupt meetings will be removed.
• This is a community-driven group and does not represent or endorse specific interest groups.