Up to now, I wrote about how recent AI developments are changing data science interview loops from a hiring manager’s perspective.
I went through several interviews myself. Job hunting is at all times stressful. Being on the opposite side, I noticed how much ChatGPT could streamline and speed up the interview preparation process for data scientists.
Due to this fact, in this text, I’ll share my ChatGPT hacks for job search and interviews with real examples.
Step 0 — Create a ChatGPT Project
Before getting began, I highly recommend making a recent project in ChatGPT to arrange all of the files and conversations. Job search isn’t a straightforward and quick process — you’ll likely have separate chats for various positions. A ChatGPT project keeps every part in a single independent folder and ensures persistent memories across all chats.
For my setup, I uploaded my resume and past projects in order that ChatGPT can higher understand my background and make tailored recommendations.
My past projects doc is a set of my best projects that may be utilized in my resume and interviews, written within the R-STAR structure. Here is one example:
R(esult): Construct an AI-based internal app that centralizes customer feedback with automated feedback classification and evaluation. That is now a critical tool for PMs and Engineers to set the product development roadmap.
S(ituation): We’ve customer feedback scattered in 20+ different data sources (NPS, CSAT, other surveys, CX Cases, In-product feedback tool, Customer Calls, etc.). The hold a number of values but are usually not being shared and analyzed broadly and effectively.
T(ask): Consolidate all the information sources and shut the feedback loop between Customer Support and Product teams.
A(ction): 1. Built data pipeline to integrate all these 20+ data sources into one source of truth dataset. 2. To uncover the topcs and trends, we tried traditional NLP models (BERT), but they took a protracted time and the output wasn’t quite stable. Then we switched to OpenAI API for classification and summarization — after a number of rounds of prompt engineering, we achieved high accuracy inside per week (70% label accuracy out of 11 categories). 3. Developed an automatic pipeline to process the brand new feedback with OpenAI API each day and collaborated with eng to establish an internal server and app to make the tool easily accessible to everyone.
R(esult): One stop shop for all customer feedback, facilitated roadmap prioritization. Won Hackathon ‘Customer Love’ award and All Hands cultural point shout out.
Once the documents were uploaded, I added a project-level instruction so ChatGPT could act as my personalized profession coach. Here is my prompt:
I’m applying for Data Scientist roles in the US.
You might be an authority profession coach specializing in data science job search and interview preparation.Analyze my resume, portfolio, and past projects to completely understand my background, skills, and expertise.
Your responsibilities include:
1. Job Search Support: Analyze job descriptions and discover skill or experience gaps.
2. Resume & Portfolio Refinement: Suggest targeted improvements and help tailor them to specific roles.
3. Interview Preparation: Create structured study and preparation plans for each technical and behavioral interviews.
4. Mock Interviews: Conduct realistic mock interviews with feedback and scoring.Please maintain an expert tone and at all times provide practical, detailed, and actionable guidance.
Step 1 — Application
Analyze Job Descriptions and Customize Resume
The job market today could be very competitive. Due to this fact, it is crucial to rigorously read the job description and customize your resume accordingly. ChatGPT makes this process much faster.
Within the sections below, I’ll use the Data Scientist, Platform and B2B Products position at OpenAI for example. Disclaimer — I did not likely apply for this position, but feel it could possibly be fun to make use of an OpenAI opening to higher illustrate the ideas in this text 🙂
Step one I took was to share the job description with ChatGPT and ask it to assist me understand this role higher, including its domain, data science use cases, and key skills. Should you are usually not sure if a task is a great fit in your background, you too can ask ChatGPT to judge for you. For instance, below I asked it to match two different openings at OpenAI and make a suggestion.
Once you’ve got a great understanding of the position and have made up your mind to use, ChatGPT can quickly update your resume based on the domain and required skills. Within the screenshot below, it generated a customized version of my resume and highlighted probably the most relevant experiences. It’s also possible to add more specific instructions on what and the way you wish it to alter, and keep iterating with ChatGPT.
One thing to notice, though — I did spot some obvious mistakes, reminiscent of the reversed title sequence under my employer’s name. Be sure you don’t just copy and paste every part it writes, but read through your recent resume line by line and proper any flawed or hallucinated contents 🙂
Within the job application process, you too can use ChatGPT to update your LinkedIn profile, edit cover letters, and draft referral request messages.
Step 2 — Interview Preparation
Now, let’s assume your applications got some traction with the assistance of ChatGPT. Congratulations! Time to prepare in your interviews.
1. Understand the Business Context
I don’t often go straight to mock interviews. As an alternative, for each position I interviewed for, my first step of interview preparation was at all times to research the products and business models, take into consideration key metrics, and provide you with data science use cases. ChatGPT may be the proper brainstorming partner here. Let’s see an example below:
On this case, ChatGPT generated a reasonably comprehensive and detailed table by itself, summarising lifecycle stages, product focus, key metrics, and data science use cases. That being said, I feel it’s more helpful to take a stab yourself first. For instance, once I was preparing for my DoorDash interviews (my current employer), I drew a mind map and asked ChatGPT to refine it further. This hybrid approach helped me to boost my understanding and spot gaps.
2. Product Case Interview Preparation
Product case interviews have been increasingly vital for Data Science roles, especially given AI’s strong capability in coding. In consequence, I often spend not less than 50% of my interview preparation time here. ChatGPT can make it easier to find and create role-specific sample cases and conduct mock interviews with you.
Within the screenshot below, I simply described the common topics within the product case round with query examples. The generated case interview questions followed the pattern pretty much, while tailoring to the business context of this Platform and B2B Products DS role.
With these helpful query prompts, next, you’ll be able to conduct mock interviews with ChatGPT. A mock interview generally is a very expensive service. For instance, DataInterview charges $247 for a one-hour mock interview, and an InterviewQuery premium subscription, which incorporates mock interview service, costs $79 monthly. In fact, practicing with real people has its advantages, but ChatGPT is free (assuming you’re already a subscriber) and customizes to your background!
I like practicing in real-time with the voice mode to simulate an actual interview setting — I asked ChatGPT to act because the interviewer, evaluating my responses and asking follow-up questions. Below is a screenshot of my mock interview once I was preparing for DoorDash’s onsite.
3. Behavioral Interview Preparation
ChatGPT is equally powerful for behavioral rounds. Aside from conducting mock interviews, it could possibly match your past projects to common behavioral query topics, reminiscent of handling conflicts, leadership, cross-functional collaboration, and prioritization, and refine the storyline for concise and compelling interview responses.
4. Create Interview Preparation Plan
ChatGPT is often known as a great planning assistant. Seeing every part it could possibly do above, you’ll be able to provide your timeline and focus areas to get a concrete interview preparation plan and a each day checklist.
Step 3 — After Interviews: Offer Evaluation and Negotiation
The last stage of the job search process is the offer evaluation and negotiation. I do know you’re very excited to receive the offer, but don’t just accept it as-is. Based on a study, 73% of U.S. employers say they’re open to negotiating salary on initial offers, but 55% of candidates don’t ask for more. As an information skilled, I’m sure you understand the ability of compounding — even a moderate increase compounds over time through raises, bonuses, and equity.
ChatGPT can make it easier to research similar offers within the industry, compare compensation packages, draft recruiter replies, and prepare negotiation scripts.
Final Thoughts
The job search process can feel overwhelming, but tools like ChatGPT turn it right into a more structured journey. For me, ChatGPT acted as my personal profession coach, helping me stay organized, efficient, and assured.
Listed below are the important thing takeaways:
- Before getting began: Use a ChatGPT Project to centralize your job search materials and context. Upload your resume and past projects so ChatGPT can tailor advice.
- Job application: Let ChatGPT analyze job descriptions and customize your resume. Don’t skip the human review — at all times fact-check your content.
- Interview preparation: Brainstorm business metrics and data science use cases with ChatGPT and conduct mock interviews using voice mode to simulate conversation.
- Offer evaluation: Ask ChatGPT to research comparable offers and draft negotiation strategies.
Should you are considering or in the midst of job hunting, I hope my suggestions make it easier to make full use of those AI tools at every stage and facilitate your profession!
