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Data Scientist – People Analytics
| Company | Blackstone |
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| Location | New York, NY, USA |
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| Salary | $125000 – $180000 |
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| Type | Full-Time |
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| Degrees | Bachelor’s, Master’s |
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| Experience Level | Mid Level, Senior |
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Requirements
- A strong interest in Human Resources/IO Psychology and the drive to help us build a more effective workforce
- 4+ years of professional experience in data science, with a strong emphasis on providing analytics solutions directly to clients
- 3+ years of experience in Python or R conducting statistical analysis or developing predictive models
- 3+ years of experience using SQL working with relational databases and data warehousing
- Strong understanding of statistical concepts (correlation, regression, T-test, ANOVA), research methods and experimental design
- Experience with supervised and unsupervised learning techniques, such as regression, classification, clustering, and dimensionality reduction
- Strong communication and data presentation skills
- Some experience with LLM/text analysis, or an interest in learning
- Bachelor’s or Master’s Degree in Data Science, Statistics, Math, Computer Science, or related
Responsibilities
- Conduct advanced statistical analyses and research focused on talent, recruiting, and organizational effectiveness, leveraging quantitative and qualitative data
- Develop and implement predictive models to identify patterns and trends in hiring, employee behavior, performance and retention
- Apply analytical and problem-solving skills to navigate ambiguity and develop recommendations for better business decisions
- Design, develop, and deliver compelling reporting solutions and dashboards to enhance decision-making for our Businesses and HR partners
- Continuously improve our reporting and analytics framework by contributing to the roadmap, documenting internal processes, and standardizing metrics and definitions
- Build tools and audits to enhance business intelligence and improve data integrity and efficiency in reporting processes
Preferred Qualifications
- Familiarity with version control systems, such as Git
- Experience with cloud platforms (e.g., AWS, Azure) and big data tools (e.g., Spark, Hadoop)
- Knowledge of technical documentation and project planning techniques
- Knowledge of data visualization tools like Tableau, Power BI, or Python visualization libraries
