Benefits:
- 401(k)
- Bonus based on performance
- Competitive salary
- Dental insurance
- Flexible schedule
- Health insurance
- Opportunity for advancement
- Paid time off
- Parental leave
- Signing bonus
- Training & development
- Tuition assistance
- Vision insurance
- Wellness resources
### 1. Determine the Type of Data You Wish to Examine
– **Identify Objectives**: Clearly define the purpose of your analysis. What questions are you trying to answer? What decisions will be informed by this data?
– **Select Data Types**: Decide on the type of data that will best serve your objectives. This could include quantitative data (numerical values) or qualitative data (descriptive information).
– **Consider Sources**: Identify potential sources of data, such as surveys, databases, public records, or online platforms. Determine whether you need primary data (collected firsthand) or secondary data (existing data collected by others).
### 2. Collect the Relevant Data
– **Data Collection Methods**: Choose appropriate methods for data collection based on your objectives. This could involve surveys, interviews, experiments, or web scraping.
– **Sampling**: If applicable, determine your sampling strategy. Decide whether you will use random sampling, stratified sampling, or another method to ensure your data is representative.
– **Data Integrity**: Ensure that the data collected is accurate and reliable. Implement measures to minimize errors during the collection process.
### 3. Refine and Organize the Data for Analysis
– **Data Cleaning**: Review the collected data for inconsistencies, missing values, or outliers. Clean the data by correcting errors, filling in missing values, or removing irrelevant entries.
– **Data Transformation**: Convert the data into a suitable format for analysis. This may involve normalizing values, categorizing qualitative data, or aggregating data points.
– **Data Structuring**: Organize the data into a structured format, such as spreadsheets or databases, to facilitate analysis. Ensure that the data is labeled clearly and logically.
### 4. Conduct the Analysis of the Data
– **Choose Analytical Techniques**: Select appropriate statistical or analytical methods based on the type of data and the questions you aim to answer. This could include descriptive statistics, inferential statistics, regression analysis, or machine learning techniques.
– **Utilize Software Tools**: Employ data analysis software or programming languages (such as Excel, R, Python, or specialized statistical software) to perform the analysis efficiently.
– **Run the Analysis**: Execute the chosen analytical methods on the organized data. Ensure that you document the process and any assumptions made during the analysis.
### 5. Interpret the Results Obtained to Extract
This is a remote position.
Compensation: $27.00 – $30.00 per hour
Built on a foundation of great brands and employees with a passion for service, our vision is to be the leading provider of essential services through empowered people, world-class customer service and convenient access. By joining ServiceMaster, you’ll be part of a talented network of employees with a shared vision.
Our environment is a diverse community where successful people work together to achieve common goals.