Manager, Business Intelligence & Analytics Salary at Manpowergroup Global Inc BETA
How much does a Manpowergroup Global Inc Manager, Business Intelligence & Analytics make?
As of March 2025, the average annual salary for a Manager, Business Intelligence & Analytics at Manpowergroup Global Inc is $199,235, which translates to approximately $96 per hour. Salaries for Manager, Business Intelligence & Analytics at Manpowergroup Global Inc typically range from $174,599 to $216,574, reflecting the diverse roles within the company.
It's essential to understand that salaries can vary significantly based on factors such as geographic location, departmental budget, and individual qualifications. Key determinants include years of experience, specific skill sets, educational background, and relevant certifications. For a more tailored salary estimate, consider these variables when evaluating compensation for this role.
DISCLAIMER: The salary range presented here is an estimation that has been derived from our proprietary algorithm. It should be noted that this range does not originate from the company's factual payroll records or survey data.
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What Skills Does a person Need at Manpowergroup Global Inc?
At Manpowergroup Global Inc, specify the abilities and skills that a person needs in order to carry out the specified job duties. Each competency has five to ten behavioral assertions that can be observed, each with a corresponding performance level (from one to five) that is required for a particular job.
- Insight: Insight is the understanding cause and effect based on the identification of relationships and behaviors within a model, context, or scenario.
- Analysis: Analysis is the process of considering something carefully or using statistical methods in order to understand it or explain it.
- Leadership: Knowledge of and ability to employ effective strategies that motivate and guide other members within our business to achieve optimum results.
- Data Analytics: Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. Data mining is a particular data analysis technique that focuses on modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. In statistical applications, data analysis can be divided into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering new features in the data while CDA focuses on confirming or falsifying existing hypotheses. Predictive analytics focuses on application of statistical models for predictive forecasting or classification, while text analytics applies statistical, linguistic, and structural techniques to extract and classify information from textual sources, a species of unstructured data. All of the above are varieties of data analysis.
- Data Science: Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Data science is the same concept as data mining and big data: "use the most powerful hardware, the most powerful programming systems, and the most efficient algorithms to solve problems". Data science is a "concept to unify statistics, data analysis, machine learning and their related methods" in order to "understand and analyze actual phenomena" with data. It employs techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, and information science. Turing award winner Jim Gray imagined data science as a "fourth paradigm" of science (empirical, theoretical, computational and now data-driven) and asserted that "everything about science is changing because of the impact of information technology" and the data deluge. In 2015, the American Statistical Association identified database management, statistics and machine learning, and distributed and parallel systems as the three emerging foundational professional communities.
Related Jobs
Check more jobs information at Manpowergroup Global Inc
| Job Title | Average Manpowergroup Global Inc Salary | Hourly Rate | |
|---|---|---|---|
| 2 | Account Excecutive | $100,454 | $48 |
| 3 | Account Manager, Human Resources | $133,057 | $64 |
| 4 | Account Payable Associate | $55,293 | $27 |
| 5 | Account Receivable Representative | $53,864 | $26 |
| 6 | Accounting Administrator | $213,970 | $103 |
| 7 | Accounting Analyst | $88,568 | $43 |
| 8 | Accounting Assistant | $55,329 | $27 |
| 9 | Accounts Assistant & Manager | $58,413 | $28 |
| 10 | Accounts Controller | $281,690 | $135 |
| 11 | Accounts Executive | $85,311 | $41 |
| 12 | Accounts Payable | $55,293 | $27 |
Hourly Pay at Manpowergroup Global Inc
FAQ about Salary and Jobs at Manpowergroup Global Inc
The average hourly pay is $96. The salary for each employee depends on several factors, including the level of experience, work performance, certifications and skills.
According to the data, the highest approximate salary is about $216,574 per year. Salaries are usually determined by comparing other employees’ salaries in similar positions in the same region and industry.
According to the data, the lowest estimated salary is about $174,599 per year. Pay levels are mainly influenced by market forces, supply and demand, and social structures.
There are various ways to increase the wage. Level of education: An employee may receive a higher salary and get a promotion if they obtain advanced degrees. Experience in management: an employee with supervisory experience can increase the likelihood to earn more.