Healthcare Data Scientist Salary at Linkedin Corp BETA
How much does a Linkedin Corp Healthcare Data Scientist make?
As of April 2025, the average annual salary for a Healthcare Data Scientist at Linkedin Corp is $112,657, which translates to approximately $54 per hour. Salaries for Healthcare Data Scientist at Linkedin Corp typically range from $90,403 to $124,467, 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 Linkedin Corp?
At Linkedin Corp, 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.
- Analysis: Analysis is the process of considering something carefully or using statistical methods in order to understand it or explain it.
- Data entry: Transcribing information into an electronic medium such as a computer or other electronic device.
- Health care: Health care or healthcare is the improvement of health via the prevention, diagnosis, treatment, amelioration, or cure of disease, illness, injury, and other physical and mental impairments in people.
- Data Management: Data Management comprises all disciplines related to managing data as a valuable resource. The concept of data management arose in the 1980s as technology moved from sequential processing (first cards, then tape) to random access storage. Since it was now possible to store a discreet fact and quickly access it using random access disk technology, those suggesting that data management was more important than business process management used arguments such as "a customer's home address is stored in 75 (or some other large number) places in our computer systems." However, during this period, random access processing was not competitively fast, so those suggesting "process management" was more important than "data management" used batch processing time as their primary argument. As software applications evolved into real-time, interactive usage, it became obvious that both management processes were important. If the data was not well defined, the data would be mis-used in applications. If the process wasn't well defined, it was impossible to meet user needs.
- Data Analysis: 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.
Related Jobs
Check more jobs information at Linkedin Corp
| Job Title | Average Linkedin Corp Salary | Hourly Rate | |
|---|---|---|---|
| 2 | 2 Engineer | $181,683 | $87 |
| 3 | 3D Graphic Designer | $92,459 | $44 |
| 4 | Abinitio Developer | $138,362 | $67 |
| 5 | Academy Manager | $103,672 | $50 |
| 6 | Account Administrator | $60,320 | $29 |
| 7 | Account Coordinator | $155,493 | $75 |
| 8 | Account Director, Enterprise | $282,639 | $136 |
| 9 | Account Manager, Commercial Sales | $195,435 | $94 |
| 10 | Account Manager, Retail | $91,867 | $44 |
| 11 | Account Manager, Support | $118,875 | $57 |
| 12 | Account Manager, Wholesale | $198,906 | $96 |
| 13 | Account Receivable | $71,150 | $34 |
Hourly Pay at Linkedin Corp
FAQ about Salary and Jobs at Linkedin Corp
The average hourly pay is $54. 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 $124,467 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 $90,403 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.