DataFramed [DataFramed Careers Series #4]: Acing the Data Science Interview
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Jun 2, 2022 
Jay Feng, co-founder of Interview Query, shares his insights on acing data science interviews. He discusses the anatomy of these interviews, revealing common misconceptions and critical mistakes candidates make. The importance of showcasing communication skills and business acumen is highlighted, suggesting that technical know-how alone isn't enough. Jay also covers strategies for negotiating salaries, emphasizing the value of knowing your worth, and shares tips for new data professionals to make an impactful start in their careers.
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Prioritize Technical Topics
- Understand the specific data science role you're applying for.
- Analyze the job description and research past interview experiences at the company.
Seek Clarification
- If a company lacks online resources, talk to the recruiter or hiring manager.
- Ask them about the interview process and what skills they test for.
Common Technical Mistake
- Candidates often jump into technical details too quickly.
- They should first gather more information and context to understand the problem fully.