Location – Bangalore
About employer– Honeywell
The Predictive Analytics Analyst reports to the Predictive Analytics Director and is responsible for primarily executing data mining and data analysis for Predictive Analytics projects and programs. Using statistical and data mining tools, this role will identify significant factors/signals, establish regression and classification models, and apply machine learning algorithm to predict key HR indicators such as turnover, quality of hire, job performance, and employee engagement level for HR across Honeywell.
- Based on the project scope identified by Predictive Analytics Director or Leader, develop data collection plans and gather the data set from reporting team or HR & Finance systems.
- Using statistical and data mining tools, drill down the data gathered and identify key factors to attribute to predicted value such as turn over, quality of hire, job performance and employee engagement level.
- Partnering with Reporting team and Analytics team, validate data accuracy before and after the analysis.
- Continuously learn cutting edge statistics, data mining and machine learning technology, share the learning with the team and apply the knowledge to the projects.
- Proactively monitoring HR data to identify opportunities for additional analysis.
- Recommend enhancements to HR reporting tools to do advanced analytics; work with HRIT on implementation.
- Develop and execute control plans to monitor the accuracy and effectiveness of the predictive models and optimization solutions for HR and Business.
Qualification and Skills Required
- Bachelors degree; Masters degree or relevant certification desired
- Data Science
- Data Mining
- Computer Science in Artificial Intelligence or Machine Learning
- 2~3 years work experience in an Analytics, Statistics, Data Mining or Marketing Analytics function is a plus.
- Additional Qualifications
- Demonstrated ability to translate data into meaningful information.
- Ability to visualize the data & solutions, as simple and easy to understand for the customers.
- Strong skills in statistical and data mining tools such as R, SPSS or Minitab.
- Strong communications skills – oral and written.
- Strong interest in applying statistics, machine learning or data mining into People.
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