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Career Resources for Data Science, Machine Learning, Big Data and Business Analytics Career Repository

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Data Science and Machine Learning Career

This repo is designed to give prospective analytical employees some additional information that might help with the job search. It takes inspiration from Conor Dewey, Academic, CIO, ZuZooVN, Maxim, ryanswanstorm

Platforms:

  1. Triplebyte - Take a quiz. Get offers from multiple top tech companies at once - includes a machine learning track.
  2. Toptal - Developers seeking to gain entry into the Toptal community are put through a battery of personality and technical tests.
  3. Hired - Hired matches employers with qualified candidates through a combination of in-house algorithms and online support.
  4. Kaggle - Take your competition skills to an employer.
  5. Direct - Contact companies directly (not recommended)
  6. AI Jobs - Jobs in AI and Big Data
  7. Analytics Jobs UK - Support analytics workers with useful career information

Reviews:

  • Glassdoor - Best employee narratives.
  • Indeed - Best coverage.
  • Kununu - Best well-rounded infromation.
  • Comparably - Best comparison functionality.
  • InHerSight - Best female-friendly perspective.
  • Paysa - Are you getting paid your market salary.
  • Levels.fyi - Compare career levels across companies.

Respected Online Courses

Competitions

Respected Packages (From 300 listings)

Respected Skill Tags (From 300 listings)

  • Machine Learning
  • Statistics
  • Applied Mathematics
  • Big Data
  • Deep Learning
  • Data Visualisation
  • Data Analysis
  • NLP
  • ETL
  • Computer Vision

Respected Bootcamps

Name Switchup Rating Cost Locations
NYC Data Science Academy 4.87 $17,600 New York City and online
Dataquest 4.92 $29 for a basic monthly subscription; $49 for a premium monthly subscription Online
RMOTR 4.91 $349 per month; one-week free trial available Online
Springboard 4.73 $499 per month Online
General Assembly 3.98 $3,950 for the part-time online courses; $15,950 for the in-person full-time immersive bootcamp program Dallas, Providence, San Diego, San Francisco, Seattle, New York City, Washington (D.C.), Austin, Los Angeles, Atlanta, Denver, Chicago, London, Singapore, Hong Kong, Sydney, Melbourne, Boston, Santa Monica and online
Metis 4.91 $750 per course Chicago, New York City, San Francisco, Seattle, Singapore and online
Data Science Dojo 4.91 Packages range from $3,799 to $4,499 with the option for flexible payment plans Seattle, Washington (D.C.), Austin, Chicago, New York City, Toronto, Barcelona, Bucharest, Las Vegas, Singapore, Dubai, Amsterdam, Pretoria and Bangalore
Thinkful 4.89 $16,000 for the full-time course; $9,500 for the flexible six-month course Washington (D.C.), Philadelphia, Houston, Portland, Dallas, Los Angeles, Phoenix, San Diego, Atlanta, Miami, Tampa, Chicago, Raleigh-Durham, Denver, Boston, San Francisco, Detroit, Salt Lake City, Seattle, Minneapolis, Austin and online
DataCamp 4.61 $25 per month Online
The Dev Masters 4.97 $4,995 for project-based learning; $6,995 for the mastering applied data science program; $3,500 for the data science for professionals program. Los Angeles, Orange County and Santa Monica
Ubiqum Code Academy 4.85 $9,000 Amsterdam, Barcelona, Berlin and Madrid
Level 4.52 $4,495 for the introductory data analytics course; $7,995 for the intermediate data analytics program Boston, Charlotte, San Francisco, San Jose, Seattle, Toronto and online
The Data Incubators 4.52 Free for accepted fellows Boston, New York City, San Francisco, Washington (D.C.) and online
Jedha 5.0 $3,595 for the full stack data science program; $995 for the fundamentals in data science Lyon and Paris
Science to Data Science 4.83 £800 registration fee, after that the course is free if you are accepted London and online

Podcasts

Popular Careers

Groups

Linkedin Groups

  • Data Mining, Statistics, Big Data, Data Visualization, and Data Science
  • Artificial Intelligence, Deep Learning, Machine Learning
  • Big Data, Analytics, Business Intelligence & Visualization Experts Community
  • KDnuggets Machine Learning, Data Science, Data Mining, Big Data, AI
  • Cloud Computing, SaaS & Virtualization
  • Data Warehouse — Big Data — Hadoop — Cloud — Data Science — ETL
  • Artificial Intelligence, Deep Learning and IoT
  • SQL Server Business Intelligence(BI)
  • Internet of Things
  • Bank and Finance Technology — FinTech Banking Systems Financial Executives
  • Cloud Computing
  • Python Community
  • Python Data Science and Machine Learning

Reddit:

  • Dataengineering
  • Dataisbeautiful
  • Datasets
  • Datascienceproject
  • Learndatascience
  • Learnprogramming
  • Learnpython
  • Machinelearning
  • Learnmachinelearning
  • Python
  • Computervision
  • learnprogramming
  • Businessintelligence
  • programming
  • Scala
  • AWS
  • bigdata
  • SQL

Main Industry Companies

  • Artificial Intelligence
    • Google
    • Amazon
    • Microsoft
    • IBM
    • Salesforce
    • Intel
    • OpenAI
  • Biotechnology
    • AbbVie
    • Aduro Biotech
    • Genentech
    • Illumina
    • Jounce Therapeutics
    • Merck & Company
    • Somalogic
  • Finance
    • JP Morgan
    • Barclays
    • Goldman Sachs
    • ING
    • Two Sigma
    • Renaissance
    • Citadel
    • AQR
    • Bridgewater
    • DE Shaw
    • Blackstone
    • Bain Capital
  • Health Care
    • Berg
    • CHAMPS Oncology
    • DarkMatter2db
    • Health Catalyst
    • Kairoi Health
  • Insurance
    • Allianz SE
    • UnitedHealth
    • Anthem
    • Humana
    • Centene Corporation
  • Logistics
    • Amazon
    • Wallmart
    • Tesla
    • Convoy
    • Flexport
    • FedEx
    • CargoX
    • 6 River Systems
    • Nuro
  • Marketing and Advertising
    • Amazon
    • Google
    • Facebook
    • Asos
    • Alibaba
    • InsideSales.com
    • Conversica

Thought Leaders

I don't know the other areas that well, send my your thought leaders by pull request.

Highest Paying Data Science Jobs

Communities

Conferences

  • Neural Information Processing Systems (NIPS)
  • International Conference on Learning Representations (ICLR)
  • Association for the Advancement of Artificial Intelligence (AAAI)
  • IEEE Conference on Computational Intelligence and Games (CIG)
  • IEEE International Conference on Machine Learning and Applications (ICMLA)
  • International Conference on Machine Learning (ICML)
  • International Joint Conferences on Artificial Intelligence (IJCAI)
  • Association for Computational Linguistics (ACL)

Journals, Publications and Magazines

Colleges

Newsletters:

Data Science Weekly

Data Science Weekly is definitely a fan-favorite, and for good reason. The newsletter started in 2013 and has pumped out 276 consistent issues since. It starts off with an Editor Picks section and quickly moves onto listing a bunch of data science articles and videos. Furthermore, it includes a section for job openings, tutorials, and books as well. Sent every Thursday, this one is well worth your time. Check out a recent issue.

O’Reilly Data Newsletter

You have probably heard of O’Reilly Media in one way or another. Personally, I have a collection of their books sitting on my desk at all times. They also publish ebooks, host conferences, and offer other learning solutions. Their data-focused newsletter delivers 10 links each week that range from news to tutorials to white-papers.

Data Elixir

Data Elixir takes a similar approach, breaking things down into a wide-ranging collection of weekly news, insights, tools & techniques, resources, and data visualization. The newsletter goes out to over 29,000 subscribers and is delivered every Tuesday. Check out a recent issue.

Data Machina

Data Machina is a more technical newsletter that breaks down links by technology, hitting on topics from R to blockchain to algorithms. There’s really a little bit of everything here. I subscribe to the free version, sent every two weeks but it looks like you can pay to receive the newsletter every week if you would like. Check out a recent issue.

The Analytics Dispatch

Mode offers a number of enterprise data solutions, but they also put out a pretty good data newsletter every week. They primarily focus on articles that catch their eye around the community but also include a section for featured data jobs as well. Check out a recent issue.

Machine Learnings

As you might have guessed, Machine Learnings focuses on ML and AI news primarily. I particularly enjoy the Awesome and Not Awesome sections that give bite-sized news if you’re in a rush. Others seem to like it as well, as the newsletter boasts 40,000+ subscribers. Check out a recent issue.

The Data Science Roundup

Another newsletter that has been around for some time, The Data Science Roundup has 177 published issues and over 7,000 subscribers to date. This newsletter takes a more concise approach, offering 5 or so links each week with an insightful reflection written on each article. Check out a recent issue.

Hacker News Digest

Not a data science newsletter per se, but a valuable resource nonetheless. Like most people in tech, I love Hacker News. However, I had a hard time keeping up with it, until I found this. You can dictate the frequency and amount of links that are sent to you based on the number of upvotes on each post.

Kaggle Newsletter

This newsletter contains any recent blog posts, interviews, or news regarding Kaggle, everyone’s favorite machine learning competition site. It also includes links, resources, meetups, and job openings around the community. I couldn’t find a subscribe link for this one, pretty sure Kaggle automatically subscribes you when you make an account.

Stratechery: The Daily Update

Stratechery’s Daily Update is a little different than the others in that it’s a paid, daily membership. Not a traditional data science newsletter, these reports focus on tech strategy think-pieces. It’ll run you around $10/month, a little less if you pay yearly. This is one of the few places where I gladly pay for written content, Medium being the other. There’s also plenty of free essays available on the site. Check out this post and others to get a feel for it.

Import AI

Import AI leans heavily on technical machine learning and AI resources, often white-papers and recent research results. The issues also include an impressive amount of analysis. Even if none of that is your thing, make sure to read the Tech Tales section at the end for an always-interesting futuristic story. Check out a recent issue.

The Wild Week in AI

Similar to Import AI, this newsletter covers technical machine learning and AI tutorials, projects, research papers, and news. Delivered a bit sporadically, The Wild Week in AI has over 17,000 subscribers if that’s any indication of the content. Check out a recent issue.

Data Is Plural

Data Is Plural is delivered weekly, focusing solely on interesting datasets for you to explore or use in your next side-project. There’s also a pretty awesome Google doc that serves as the archive for all these datasets dating back to 2015. Check out a recent issue.

TDS Weekly Selection

Last but not least, the team at Towards Data Science puts out both weekly and monthly digests of the most popular posts on the publication. You can receive these emails by accepting Letters from TDS if you go to the dropdown found on their homepage. Check out a recent issue.

Project Inspiration:

Data is Beautiful I could spend hours just browsing this subreddit of data visualizations. You’ll be interested in all of the unique ideas and questions that people think up. There’s also monthly challenge where a dataset is chosen, and users are tasked with visualizing it in the most effective way possible. Sort by best all time for instant gratification.

Kaggle I would be remiss if I didn’t mention the poster child of online data science. There’s a couple ways to use Kaggle effectively for inspiration. First, you can look at the trending datasets and think of interesting ways to leverage the information. If you’re more interested in machine learning and the examples themselves, the kernels feature has gotten better and better over time.

The Pudding It really is true that visual essays are an emerging form of journalism. The Pudding embodies this movement like none other. The team uses original datasets, primary research, and interactivity in order to explore tons of interesting topics.

FiveThirtyEight A classic, but still good to this day. I mean come on, Nate Silver is the man. The data-driven blog touches on everything from politics to sports to culture. Not to mention, they just revamped their much improved data export page.

Towards Data Science Lastly, I’ve got to give a shoutout to the TDS Team for bringing together this community of smart people with a passion for achieving things and helping others grow in data science. Browsing recent stories will bring you more than a few interesting project ideas on any given day.

Technical Prep

Interviews

General

Algorithmic Coding & Python

Statistics and Probability

Data Manipulation & SQL

Data Analysis & Pandas

Machine Learning

Product and Experimentation

Big Data

Tech Interview Handbook

Python

Scala

MongoDB

MySQL

SQL

Business Analytics Companies - 2019 Glassdoor Rankings

"Best to work for"

Arcadia Data, FiveTran, InfluxData, Dataiku, Confluent, Redis Labs, StreamSets, Looker, Periscope Data, ThoughtSpot, Alation, Dremio, H2O.ai and SAP

"Great to work for"

Pivotal Software, Domo, Salesforce, SiSense, Google, Couchbase, Microsoft, DataStax, Actifio, MongoDB, Databricks, MemSQL, Informatica, Talend, Qubole

"Good to work for"

Tamr, VoltDB, Sumo Logic , Reltio, Trifacta, DataRobot, MarkLogic, Delphix, EnterpriseDB, Dell EMC, Tableau Software, Amazon Web Services, Paxata, Big Squid, Kyvos Insights, RapidMiner, TIBCO

"It is a job"

Qlik, IBM, SAS, Magnitude Software, Zaloni, Splunk, Information Builders, Hewlett Packard Enterprise, MicroStrategy, Cloudera, Oracle, Alteryx, Logi Analytics, GoodData, MapR Technologies, Syncsort, SnapLogic, Outlier, Zoomdata, Hitachi Vantara/Pentaho, Datameer

Most Data Scientists (per Linkedin Recruiter)

  • IBM
  • Microsoft
  • Accenture
  • Amazon
  • Tata Consultancy
  • Cognizant
  • Google
  • Capgemini
  • Infosys
  • Oracle

Most Numerous Data Science Skills (per Linkedin Recruiter)

  • Data Analysis
  • Python
  • R
  • Machine Learning
  • Statistics
  • Data Mining
  • Big Data
  • Deep Learning
  • Data Visualisation
  • NLP

Most Numerous Data Science Industries (per Linkedin Recruiter)

  • Information Technology and Services
  • Computer Software
  • Research
  • Higher Eductation
  • Financial Services
  • Telecommunications
  • Management Consulting
  • Internet
  • Banking
  • Insurances

Resume

Sponsors

Firmai.org is a project that focuse on the aggregation of open source AI-BI applications. FirmAI envisions a future of open data access and the facilitation of small-medium enterprise automation.

Tired of technical phone screens? Take Triplebyte’s quiz and go straight to final onsite interviews! Also check out Triplebyte’s Salary Tool! They use real data from actual offers made to Triplebyte engineers. A few of the companies that use Triplebyte include Adobe, Robinhood, Box, Dropbox, Instacart, Evernote, Hipmunk, Grammarly & Palantir

r/datascienceproject is a subreddit where you can share all your data science projects. There is no restrictions on self promotion. Let the best post rise to the top. One rule, it has to relate to a data science project.

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Career Resources for Data Science, Machine Learning, Big Data and Business Analytics Career Repository

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