Data Scientist

Your job

Drive a deep and complete understanding of our users through the application of a mix of machine learning, statistics, and analytics skills. Use data to track, understand, and improve user performance and translate that into strategic insights and recommendations. Assist the Community and Identity Foundation team with data analysis and aid in making data-informed prioritization decisions. Work on Glassbowl dashboard creation and maintenance:
Building and maintaining a dashboard to track key metrics and provide insights on user engagement and retention for the Glassbowl product. Content Coverage between Fishbowl and Glassdoor:
Conducting an analysis to compare the content coverage between Fishbowl and Glassdoor and providing recommendations on user cohort to target. Maintain Key metric report for Sr Execs for weekly:
Creating and maintaining a report for senior executives that tracks key metrics such as user engagement and revenue, and providing analysis and insights on a weekly basis. Improve user engagement and retention through data-driven decision making. Increase the efficiency and effectiveness of the Community and Identity Foundation team. Identify new opportunities for user acquisition through data analysis.

Telecommute permitted from anywhere in the United States.

Minimum

Job Requirements:

• Master’s Degree or foreign degree equivalent in Data Science, Statistics, Applied Mathematics, Computer Science, Business Analytics, Business Intelligence or related field.
• One (1) year of experience in the job offered or in a Data Scientist-related occupation.
• Position requires one (1) year of experience in the following skills:
• 1. Statistical Analysis Methods such as Experimentation, A/B Testing, Designing, conducting, interpreting A/B tests for product analytics, Statistical Analysis Techniques, Statistical tests or distributions;
• 2. Programming Languages such as:
  Python or R for data manipulation or analysis;
• 3. Machine Learning Algorithms such as k‑NN, Naive Bayes, SVM, or Decision Forests;
• 4. Tools for data preprocessing and cleaning;
• 5. SQL for complex database queries or data extraction;
• 6. Hadoop, Spark, or similar technologies for handling large datasets;
• 7. Tools like Tableau or Power BI; and
• 8. Libraries like Matplotlib or Seaborn.

Multiple positions available.

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Salary Range: $102,400-$153,600 per year.

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