About us
Diversity in Data Science hosts educational events, professional networking, and skill building opportunities. The community is focused on supporting and building diversity in data science, and other data-related fields. We provide educational opportunities to empower minorities and marginalized groups.
Upcoming events
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WiDS: Technical Interview Prep Session
·OnlineOnlineWiDS: Technical Interview Prep Session
Join us for an engaging VIRTUAL practice session dedicated to sharpening your technical interview skills. This is a fantastic opportunity to practice in a supportive environment and receive constructive feedback from peers.
NOTE: This event requires active participation, so we ask all attendees come prepared to have cameras and microphones on during the practice rounds.
This session is specifically designed for Data Analysts, Data Scientists, Data Engineers, Machine Learning Engineers, and similar roles preparing for technical interviews in data-related fields.
What to Expect:
Participants will be organized into groups of three, with each 45-minute round structured into three 15-minute rotations. Each participant will experience all three roles during every round:- Interviewer (15 min): Conduct a technical interview, pose questions, and deliver constructive feedback using provided rubrics and problem solution
- Interviewee (15 min): Respond to technical questions while articulating your problem-solving approach
- Observer/Partner (15 min): Collaborate with the interviewee to solve or provide brainstorming support
Each participant will cycle through all three roles in Round 1, then repeat the process with new questions in Round 2.
A collaborative coding platform will be provided with support for Python, Java, JavaScript, C++, R, and SQL. Participants may select coding questions at their preferred difficulty level (Easy, Medium, or Hard) or opt for non-coding technical DS/ML questions. Answer rubrics and follow-up question guidelines will be provided to facilitate structured, meaningful feedback.
Topics Covered:
- Coding: Data structures & algorithms
- Non-Coding: Statistics, ML fundamentals, A/B testing, experimentation, metrics design
Schedule:
- 5:15 - 5:30 PM: Greetings & Networking
- 5:30 - 6:15 PM: Round 1 - Technical Interview Practice (45 min)
- 6:15 - 6:30 PM: Break
- 6:30 - 7:15 PM: Round 2 - Technical Interview Practice (45 min)
- 7:15 - 7:30 PM: Networking & Farewells
How to Prepare:
- Review fundamentals: Brush up on core concepts in your chosen track (coding or non-coding DS/ML topics)
- Practice explaining your thought process: Focus on articulating your reasoning clearly and logically
- Test your setup: Ensure your camera, microphone, and internet connection are working properly
- Choose your difficulty level: Decide whether you'll focus on Easy, Medium, or Hard coding questions, or non-coding technical questions
- Be ready to give and receive feedback: Approach the session with an open, growth-oriented mindset
Preparation Resources:
Statistics & ML Fundamentals:- StatQuest with Josh Starmer - Excellent video explanations of statistical concepts and ML algorithms
- Machine Learning Interview Guide - Comprehensive GitHub repo covering ML concepts, case studies, and interview questions
- Introduction to Statistical Learning - Free textbook with R/Python labs
A/B Testing & Experimentation:
- Trustworthy Online Controlled Experiments - Industry-standard resource on A/B testing
- Evan Miller's A/B Testing Resources - Statistical foundations and practical tools
- Netflix Tech Blog - Experimentation - Real-world examples from industry leaders
Coding Practice:
- LeetCode - Practice problems organized by topic and difficulty
- HackerRank - Statistics and data science focused tracks
- StrataScratch - Data science and SQL interview questions from real companies
General Interview Prep:
- Chip Huyen's ML Interviews Book - Comprehensive guide to ML system design and interviews
- Data Science Interview Questions - Curated list of DS interview questions and resources
WiDS Puget Sound is independently organized by Diversity in Data Science to be part of the mission to increase participation of women in data science and to feature outstanding women doing outstanding work.
Register here on Luma: https://luma.com/pam0gs7d
1 attendee
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