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It defines what data science entails and outlines roles and industry contexts, then walks readers through nine interview paths, including recruiters, events, portfolios, open data, and competitions. The guide details preparation steps, what to expect across phone screens, take-home work, and onsite stages, and the categories of questions covering behavioral, mathematics, statistics, and scenarios. 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It frames the work as more than salary and work-life balance.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"What are the main stages readers should expect in a data science interview?",{"text":118,"@type":114},"The guide outlines typical steps including a phone screen, a take-home assignment, calls with hiring managers, onsite interviews, technical challenges, and interviews with executives. It also groups how evaluation is done through multiple question categories.",{"name":120,"@type":111,"acceptedAnswer":121},"How should readers handle offers and follow up after interviews?",{"text":122,"@type":114},"It covers handling offers, company culture, team, location, and negotiating salary. After interviews, it recommends sending a follow-up thank-you note, sharing thoughts on what the interviewer brought up, and providing relevant work or homework.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},391614,1790364969,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":19,"category_name":20,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":140,"language":141,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":67,"update_tm":145,"read_time":146,"preview_page_count":4},962090893776,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Table of Contents  \nTable of Contents Introduction  \nWhat is Data Science?  \nDifferent Roles within Data Science How Different Companies Think About Data Science  \n1 Early stage startups (200 employees or fewer) looking to build a data product  \n2 Early stage startups (200 employees or fewer) looking to take advantage of their data  \n3 Mid size and large Fortune 500 companies who are looking to take advantage of their data  \n4 Large technology companies with well established data teams Industries that employ Data Scientists  \nGetting a Data Science Interview Nine Paths to a Data Science Interview  \nTraditional Paths to Job Interviews  \n1 Data Science Job Boards and Standard Job Applications  \n2 Work with a Recruiter  \n3 Go to Job Fairs  \nProactive Paths to Job Interviews  \n4 Attend or Organize a Data Science Event  \n5 Freelance and Build a Portfolio  \n6 Get Involved in Open Data and Open Source  \n7 Participate in Data Science Competitions  \n8 Ask for Coffees, do Informational Interviews  \n9 Attend Data Hackathons  \nWorking with Recruiters  \nHow to Apply  \nCV vs LinkedIn  \nCover Letter vs Email  \n\n| [www.springboard.com](www.springboard.com) | ULTIMATE GUIDE TO DATA SCIENCE INTERVIEWS | 1 |\n| --- | --- | --- |\n\nHow to get References and Your Network to Work for You Preparing for the Interview  \nWhat to Expect  \n1 The Phone Screen  \n2 Take home Assignment  \n3 Phone Call with a Hiring Manager  \n4 On site Interview with a Hiring Manager  \n5 Technical Challenge  \n6 Interview with an Executive  \nWhat a data scientist is being evaluated on  \nThe Categories of Data Science Questions  \nBehavioral Questions  \nMathematics Questions  \nStatistics Questions  \nScenario Questions  \nTackling the Interview  \nConclusion  \nWhat Hiring Managers are Looking For Interview with Will Kurt (Quick Sprout)  \nInterview with Matt Fornito (OpsVision Solutions)  \nInterview with Andrew Maguire (PMC/Google/Accenture)  \nInterview with Hristo Gyoshev (MasterClass)  \nConclusion  \nHow Successful Interviewees Made It Sara Weinstein  \nNiraj Sheth  \nSdrjan Santic  \nConclusion  \n7 Things to Do After The Interview  \n1 Send a follow up thank you note  \n2 Send them thoughts on something they brought up in the interview  \n3 Send relevant work/homework to the employer  \n\n| [www.springboard.com](www.springboard.com) | ULTIMATE GUIDE TO DATA SCIENCE INTERVIEWS | 2 |\n| --- | --- | --- |\n\n4 Keep in touch, the right way  \n5 Leverage connections  \n6 Accept any rejection with professionalism  \n7 Keep up hope The Offer Process  \nHandling Offers  \nCompany Culture  \nTeam  \nLocation  \nNegotiating Your Salary Facts and Figures  \nTaking the Offer to the Best First Day Templates  \nReaching out to get a referral  \nFollowing up after an interview  \nResources  \n\n| [www.springboard.com](www.springboard.com) | ULTIMATE GUIDE TO DATA SCIENCE INTERVIEWS | 3 |\n| --- | --- | --- |\n\nIntroduction  \nWhen we first wrote the Springboard Careers Guide to Data Science, we didn’t expect the engagement it’d garner. Thousands of people signed up in a few days, confirming our belief that there was a scarcity of great advice on what is an exciting but nebulous field.  \nIn speaking with more and more people, we found only a few great resources that explained how to break into a data science career. There were individual stories and collections of interview questions, but we couldn’t find a full guide to cover everything about the data science interview process from how to get an interview in the first place to how to deal with any offered positions.  \nI wanted a guide collecting perspectives from people on both sides of the table. I wanted to talk to recruiters who refer candidates, hiring managers who table offers, and candidates who had successfully made it through the data science interview to demystify the data science interview process with insights from people who had previously gone through the process. I co authored this book with Sri Kanajan a senior data scientist in New York City at a major invest","cbCaif7HZ5zNkGVp","https://ap.wps.com/l/cbCaif7HZ5zNkGVp","pdf",3397299,87,"English","# What is Data Science?\n## Different Roles within Data Science\n# Getting a Data Science Interview\n## Nine Paths to a Data Science Interview\n# Working with Recruiters\n## How to Apply\n## CV vs LinkedIn\n# Preparing for the Interview\n## What to Expect\n## The Categories of Data Science Questions\n# Tackling the Interview\n## Conclusion\n# What Hiring Managers are Looking For\n## Interview with Will Kurt (Quick Sprout)\n# How Successful Interviewees Made It\n## Conclusion\n# 7 Things to Do After The Interview\n## The Offer Process\n## Handling Offers\n## Negotiating Your Salary\n# Resources","[{\"question\":\"What does the guide say data science is and why it matters?\",\"answer\":\"It explains that data science is an exciting but nebulous field tied to solving big problems that matter, with real social impact such as addressing poverty and stopping pandemics. It frames the work as more than salary and work-life balance.\"},{\"question\":\"What are the main stages readers should expect in a data science interview?\",\"answer\":\"The guide outlines typical steps including a phone screen, a take-home assignment, calls with hiring managers, onsite interviews, technical challenges, and interviews with executives. It also groups how evaluation is done through multiple question categories.\"},{\"question\":\"How should readers handle offers and follow up after interviews?\",\"answer\":\"It covers handling offers, company culture, team, location, and negotiating salary. After interviews, it recommends sending a follow-up thank-you note, sharing thoughts on what the interviewer brought up, and providing relevant work or homework.\"}]","ULTIMATE GUIDE TO DATA SCIENCE INTERVIEWS | PDF",1790355801,219]