Heard in Data Science Interviews

Over 650 Most Commonly Asked Interview Questions and Answers

Heard in Data Science Interviews

A collection of over 650 actual Data Scientist/Machine Learning Engineer job interview questions along with their full answers, references, and useful tips

Data Science Interviews Exposed

Your One Stop Source for Data Engineers, Data Analysts, and Data Scientists Interviews

Data Science Interviews Exposed

Data Science Interviews Exposed offers data science career advice and REAL interview questions to help you get the six-figures salary jobs! A data science job is extremely rewarding. It empowers to you make real impact in the world! And besides, it offers competitive salaries, and it develops your creative as well as quantitative skills. No wonder the data science job is rated as one of the sexist jobs in 21st century. So what you are waiting for ? Are you still wondering how to join data science work force ? Are you lost in the tremendous amount of online data science courses and resources ? Are you endlessly searching online to find data science interview questions and answers? If you answer yes for any of the questions, Data Science Interviews Exposed is a book you absolutely want to read. Why? This book is written by data science professionals from Facebook, LinkedIn, Amazon, Google and Microsoft, with years of first hand working and interviewing experience. This is the first book in the industry that systematically covers everything for preparing for a data science career and interviews, and with real interview questions and detailed answers. This book provides both career guidance for entry level candidates as well as interview questions practice for intermediate candidates. Here is a full list of topics: Introduction This chapter presents an overview to the data science job market and the book organization. Find the Right Job Roles Get confused about the various data science job titles? This chapter provides a detailed description for each of them, the differences among them, as well as the guidance for choosing the one that suits you the most. Find the Right Experience Don't know how to prepare yourself with the right experience to meet the job requirements and your career goals? This chapter helps you to identify the experience you need to land your dream position. It also provides suggestions for new graduates as well as candidates from a different industry who want to transfer to data science field. Get Ready for the Interviews Think you have a clear goal and have possessed all the required skill sets, but just don't know how to get job interviews? This chapter walks you through how to build good resumes and professional profiles that would bring you the right exposure to the right person -- recruiters and hiring managers. Polish Your Soft Skills Heard of your competent peers failing job interviews and want to know why? This chapter reveals the secrets that most companies don t talk about publicly -- the soft skills. What are behavior questions, why are they important, how do you prepare for them? You will find the answer here. Technical Interview Questions An interview is not a pop quiz. You should take the time to practice on real interview problems and learn their patterns. This chapter lists eight major topics that are frequently covered by data science job interviews, associated with example interview questions for each of them. All of them are either real interview questions or adapted from real interview questions: Probability Theory Statistical Inference Dataset Manipulation Product, Metrics and Analytics Experiment Design Coding Machine Learning Brain Teasers Solutions to Technical Interview Questions This chapter attaches the solutions and thought process for each question in the previous chapter. We hope the readers can grasp the key points behind each of them, hence be able to apply the approaches to other similar questions in the real interviews.

Build a Career in Data Science

Build a Career in Data Science

Summary You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology What are the keys to a data scientist’s long-term success? Blending your technical know-how with the right “soft skills” turns out to be a central ingredient of a rewarding career. About the book Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the book. What's inside Creating a portfolio of data science projects Assessing and negotiating an offer Leaving gracefully and moving up the ladder Interviews with professional data scientists About the reader For readers who want to begin or advance a data science career. About the author Emily Robinson is a data scientist at Warby Parker. Jacqueline Nolis is a data science consultant and mentor. Table of Contents: PART 1 - GETTING STARTED WITH DATA SCIENCE 1. What is data science? 2. Data science companies 3. Getting the skills 4. Building a portfolio PART 2 - FINDING YOUR DATA SCIENCE JOB 5. The search: Identifying the right job for you 6. The application: Résumés and cover letters 7. The interview: What to expect and how to handle it 8. The offer: Knowing what to accept PART 3 - SETTLING INTO DATA SCIENCE 9. The first months on the job 10. Making an effective analysis 11. Deploying a model into production 12. Working with stakeholders PART 4 - GROWING IN YOUR DATA SCIENCE ROLE 13. When your data science project fails 14. Joining the data science community 15. Leaving your job gracefully 16. Moving up the ladder

Sex and Stigma

Stories of Everyday Life in Nevada’s Legal Brothels

Sex and Stigma

An intimate and original look at the lives of Nevada’s legal sex workers through the voices of current and former employees, brothel owners, madams, and local law enforcement The state of Nevada is the only jurisdiction in the United States where prostitution is legal. Wrapped in moral judgments about sexual conduct and shrouded in titillating intrigue, stories about Nevada’s legal brothels regularly steal headlines. The stigma and secrecy pervading sex work contribute to experiences of oppression and unfair labor practices for many legal prostitutes in Nevada. Sex and Stigma engages with stories of women living and working in these “hidden” organizations to interrogate issues related to labor rights, secrecy, privacy, and discrimination in the current legal brothel system. Including interviews with current and former legal sex workers, brothel owners, madams, local police, and others, Sex and Stigma examines how widespread beliefs about the immorality of selling sexual services have influenced the history and laws of legal brothel prostitution. With unique access to a difficult-to-reach population, the authors privilege the voices of brothel workers throughout the book as they reflect on their struggles to engage in their communities, conduct business, maintain personal relationships, and transition out of the industry. Further, the authors examine how these brothels operate like other kinds of legal entities, and how individuals contend with balancing work and non-work commitments, navigate work place cultures, and handle managerial relationships. Sex and Stigma serves as a resource on the policies guiding legal prostitution in Nevada and provides an intimate look at the lived experiences of women performing sex work.

Perspectives on Data Science for Software Engineering

Perspectives on Data Science for Software Engineering

Perspectives on Data Science for Software Engineering presents the best practices of seasoned data miners in software engineering. The idea for this book was created during the 2014 conference at Dagstuhl, an invitation-only gathering of leading computer scientists who meet to identify and discuss cutting-edge informatics topics. At the 2014 conference, the concept of how to transfer the knowledge of experts from seasoned software engineers and data scientists to newcomers in the field highlighted many discussions. While there are many books covering data mining and software engineering basics, they present only the fundamentals and lack the perspective that comes from real-world experience. This book offers unique insights into the wisdom of the community’s leaders gathered to share hard-won lessons from the trenches. Ideas are presented in digestible chapters designed to be applicable across many domains. Topics included cover data collection, data sharing, data mining, and how to utilize these techniques in successful software projects. Newcomers to software engineering data science will learn the tips and tricks of the trade, while more experienced data scientists will benefit from war stories that show what traps to avoid. Presents the wisdom of community experts, derived from a summit on software analytics Provides contributed chapters that share discrete ideas and technique from the trenches Covers top areas of concern, including mining security and social data, data visualization, and cloud-based data Presented in clear chapters designed to be applicable across many domains

Data Science and Big Data Analytics

Discovering, Analyzing, Visualizing and Presenting Data

Data Science and Big Data Analytics

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

Educating Health Professionals in Low-Resource Countries

A Global Approach

Educating Health Professionals in Low-Resource Countries

The shortage of adequately prepared health professionals is the most significant threat to world health that we face. This book, a co--publication with The Carter Center, focuses on the training of health professional educators--both teachers and practitioners--in low--resource countries at different levels of technological and material sophistication. This comprehensive book trains health educators and practitioners to improve their pedagogical skills and to increase the quality and numbers of health workers. It also assists physcians, nurses, health officers, medical lab technicians, and environmental technicians to work with different cultures and linguistic groups in any one country. For the growing number of health educators and practitioners in developed countries who teach, research, and practice within the international context, it is an essential resource. Key Features: Preface by former US President Jimmy Carter Offers teaching and learning methods evaluated and field tested through The Carter Center's Ethiopia Public Health Training Initiative with positive results in over 500 health care centers Provides both teaching and learning strategies for countries and cultures at different levels of technological and material development Presents research-based theories, evidence--based models, and critical thinking skills through active teaching and learning strategies Highlights faculty leadership in developing interdisciplinary teams and educational outcomes

Interviewing as Qualitative Research

A Guide for Researchers in Education and the Social Sciences, 4th Ed.

Interviewing as Qualitative Research

Now in its fourth edition, this popular book provides clear, step-by-step guidance for new and experienced interviewers to develop, shape, and reflect on interviewing as a qualitative research process. Using concrete examples of interviewing techniques to illustrate the issues under discussion, this classic text helps readers to understand the complexities of interviewing and its connections to broader issues of qualitative research. The text includes principles and methods that can be adapted to a range of interviewing approaches. Appropriate for individual and classroom use, the new edition has been expanded to include: clarification of important phenomenological assumptions that underlie the interviewing approach presented in the book; new sections on Long-Distance Interviewing and its implications for the relationship between interviewers and their participants; a new section on the pros and cons of Computer-Assisted Qualitative Data Analysis Software; The Ethics of Doing Good Work, is a new chapter which discusses the interplay between ethical issues in interviewing and how interviewers carry out their work as researchers.

Narrative Methods for the Human Sciences

Narrative Methods for the Human Sciences

"Cathy Riessman is the leading figure in narrative research and her new book is a delight. Covering basic issues of transcription and research credibility as well as visual data and engagingly written, it is a goldmine for students and researchers alike. If we want to make narrative research serious and revealing, it is to this book that we should turn." —David Silverman, Professor Emeritus, Goldsmiths' College, University of London "Narrative Methods for the Human Sciences provides an accessible framework for researchers — to analyse narrative texts with confidence, empathy, and humility. —NARRATIVE INQUIRY "This is a terrific book. Cathy Riessman has an encyclopedic knowledge of this field and of the participants in it. This breadth and depth of knowledge is abundantly clear throughout the book." —Susan Bell, Bowdoin College "This book has been a great source of inspiration to me and my students, not only for its methodological clarity, but also for the spirit of social activism it engenders." —Ian Baptiste, The Pennsylvania State University "Narrative Methods for the Human Sciences is an essential starting point for both students and experienced researchers interested in using narrative analysis in applied or other contexts. Written with admirable clarity, an engaging style, and supported by detailed examples of analysis, the book outlines the main methodological issues and approaches within the exciting and fast-developing field of narrative research. Even researchers already familiar with narrative methods should find the presentation of thematic, structural, dialogic/performance, and visual forms of analysis a fruitful stimulus to new research endeavours." —Brian Roberts, University of Central Lancashire, U.K. "I just had to thank you for paving the path for us new and 'hopeful' narrative researchers. I have been a student of both your books on narrative analysis, and want to thank you for your guidance from your work, and also your latest book Narrative Methods for the Human Sciences. This work and the references you have chosen for us have helped me immensely during this time in my doctoral program, especially as I enter into the analysis phase." —Maria T. Yelle, nursing doctoral candidate, University of Wisconsin-Madison Narrative Methods for the Human Sciences provides a lively overview of research based on constructing and interpreting narrative. Designed to improve research practice, it gives a detailed discussion of four analytic methods that students can adapt. Author Catherine Kohler Riessman explains how to conduct the four kinds of narrative analysis using model studies from sociology, anthropology, psychology, education and nursing. Throughout the book, she compares different approaches including thematic analysis, structural analysis, dialogic/performance analysis, and visual narrative analysis. The book helps students confront specific issues in their research practice, including how to construct a transcript in an interview study; complexities of working with materials translated from another language; defining narrative segments; relating text and context; locating oneself as the researcher in a responsible way in an inquiry; and arguing for the credibility of the case-based approach. Broad in scope, Narrative Methods for the Human Sciences also offers concrete guidance in individual chapters for students and established scholars wanting to join the "narrative turn" in social research. Key Features Focuses on four particular methods of narrative analysis: This text provides specific diverse exemplars of good narrative research, as practiced in several social science and human service disciplines. Offers guidance for narrative interviewing: The author discusses the complexities between spoken language and any written transcript. In the process, she encourages students to be mindful of the texts they construct from dialogues among speakers. Presents arguments about validation in case-based research: Riessman presents several ways to think about credibility in narrative studies, contextualizing validity in relation to epistemology and theoretical orientation of a study. Explores the differences between grounded theory methods and narrative analysis: The author clarifies distinctions between inductive thematic coding in grounded theory, and other interpretive approaches, and narrative analysis. Presents social linguistic methods for analyzing oral narrative: This text makes the approach accessible to readers not trained in social linguistics in part by providing rich examples from a number of different disciplines in the social and behavioral sciences. Employs visual methods of analysis: Riessman takes narrative research beyond the spoken or written texts by showing how exemplary researchers have connected participants' words and images made during the research process. She also discusses other research that incorporates "found" images (in archives) in a narrative inquiry. This text is designed as a supplement to the qualitative research course taught in graduate departments across the social and behavioral sciences, and as a core book in the narrative course.

Prematurity in Scientific Discovery

On Resistance and Neglect

Prematurity in Scientific Discovery

"In preparing this remarkable book, Ernest Hook persuaded an eminent group of scientists, historians, sociologists and philosophers to focus on the problem: why are some discoveries rejected at a particular time but later seen to be valid? The interaction of these experts did not produce agreement on 'prematurity' in science but something more valuable: a collection of fascinating papers, many of them based on new research and analysis, which sometimes forced the author to revise a previously-held opinion. The book should be enthusiastically welcomed by all readers who are interested in how science works."—Stephen G. Brush, co-author of Physics, The Human Adventure: From copernicus to Einstein and Beyond "Prematurity and Scientific Discovery contains interesting and insightful papers by numerous well-known scientists and scholars. It will be of wide interest, not only to science studies scholars but also to working scientists and to science-literate general readers."—Thomas Nickles, editor of Scientific Discovery, Logic, and Rationality