Tag: people analytics

What Skills Do You Need to Become an HR Analyst

Peng Wang

For work reasons, I have opportunities to interact with HR analysts everyday. I am always curious what skills one would need to become an HR analyst.

Below is an HR Analyst job summary from SHRM.org. Other names for HR Analyst include People Analytics Analyst, Workforce Analytics Specialist, Data Analyst - People Analytics, etc.

The Human Resource (HR) Analyst will collect, compile, and analyze HR data, metrics, and statistics, and apply this data to make recommendations related to recruitment, retention, and legal compliance.

SHRM.org

To become an HR analyst, one needs to have the HR-related domain knowledge. This topic will be explored in another article. Here we will just focus on technical skills, general skills, and education.

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Who Are the Top HR Analytics Influencers on Twitter

Social Network
Peng Wang
Visualizing Twitter social network of HRanalytics

Everyday people use social media such as Twitter to share thoughts and ideas. People with similar interests come together and interact on the online platform by re-sharing or replying posts they like. By studying how people interact on social networks, it will help us understand how information is distributed and identify who are the most prominent figures.

In our last post, we did a topic modeling study using Twitter feeds #HRTechConf and trained a model to learn the topics of all the tweets. In this article, we will analyze Twitter user interactions and visualize it in an interactive graph. 

Social Network is a network of social interactions and personal relationships. 

Oxford Dictionary
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Auto Generated Insights of 2019 HR Tech Conference Twitter – Part 2 (Topic Modeling)

HR Tech Conf 2019 Topics LDA
Peng Wang

In our last post, we extract #HRTechConf tweets, clean up the texts, and generate a word cloud that highlights some of the buzzwords from the conference. But, what are the tweets talking about? Without reviewing each of the 7,000 tweets, how could we find out the popular topics? Let's explore and see if tweet topics could be auto detected by developing a Latent Dirichlet Allocation (LDA) model.

Feature Extraction

Tweets or any text must be converted to a vector of numbers - the dictionary that describes the occurrence of words in the text (or corpus). The technique we use is called Bag of Words, a simple method of extracting text features. Here are the steps.

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Auto Generated Insights of 2019 HR Tech Conference Twitter – Part 1 (Word Cloud)

HR Tech Twitter Wordcloud
Peng Wang

HR Technology Conference and Expo, world's leading and largest conference for HR and IT professionals, just took place in Las Vegas, from Oct 1 - 4, 2019. An incredibly amount of HR technology topics were covered at the conference. Unfortunately not everyone could be there, including myself. Is it possible to tell what the buzzwords and topics are without being there? The answer is YES! I dig into Twitter for some quick insights.

I scrape tweets with #HRTechConf, and build Latent Dirichlet Allocation (LDA) model for auto detecting and interpreting topics in the tweets. Here is my pipeline:

  1. Data gathering - twitter scrape
  2. Data pre-processing
  3. Generating word cloud
  4. Train LDA model
  5. Visualizing topics

I use Python 3.6 and the following packages:

  • TwitterScraper, a Python script to scrape for tweets
  • NLTK (Natural Language Toolkit), a NLP package for text processing, e.g. stop words, punctuation, tokenization, lemmatization, etc.
  • Gensim, "generate similar", a popular NLP package for topic modeling
  • Latent Dirichlet Allocation (LDA), a generative, probabilistic model for topic clustering/modeling
  • pyLDAvis, an interactive LDA visualization package, designed to help interpret topics in a topic model that is trained on a corpus of text data
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Things Employees Like and Dislike About Their Companies

Employee Likes and Dislikes The Most
Peng Wang

I work in people analytics and have been wondering all the time what make employees feel great or bad about their companies. Is it money? Workload? Opportunities to grow? Or team around them? I know the answer depends on the company, but is there anything in common for companies that employees like or dislike the most?

I went to Glassdoor for help. Glassdoor is one of the world's largest growing job sites where employees anonymously review current or former employers. I did my studies based on the 6,000 companies that have an office in Vancouver, BC.

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Organizational network analysis – an experimental study

Organizational network. Credit: Wellesley Institute
Peng Wang

In every organization, people build and rely on informally-built networks seeking for information, advice, and collaborations. Often the invisible people networks are different from the formal organization hierarchy. Uncovering the informal but effective networks and understanding how information in the organization flows become crucial and enormously valuable to organization leaders.

In this article, we will briefly explain what Organization Network Analysis (ONA) is about and how to effectively measure. A small sample dataset is used to demonstrate our ONA experiment and network graph.

This post is part of a series of people analytics experiments:

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People Analytics – Attrition Predictions

hr_attrition. image credit: Vocoli
Peng Wang

According to the U.S. Bureau of Labor Statistics, 4.5 years is the average amount of time employees stay with their company today. It hurts an organization's financials and morale , considering the amount of time they spend training. Can management learn from the past attrition and manage to reduce turnovers? Answer is yes. We will build some predicative models using the fictional IBM data set which contains 1470 employee attrition records.

This post is part of a series of people analytics experiments I am putting together:

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Simple Skill-based Job Recommendation Engine

economist.com
Peng Wang

What are the most demanded skills for data scientists? Python, R, SQL, and the list goes on and on. There are many surveys and reports that show some good statistics on popular data skills. In this post, I am going to gather first-hand information by scraping data science jobs from indeed.ca, analyze top skills required by employers, and make job recommendations by matching skills from resume to posted jobs. It will be fun!

Quick summary of the project workflow:

[caption id="attachment_565" align="alignnone" width="952"]Workflow Workflow[/caption]

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