Business Intelligence Manager Salaries – Data science is a field that encompasses many different disciplines, but all of these data science roles require strong analytical skills, technical knowledge, and the ability to derive actionable knowledge from data literacy.
As more and more industries use innovative data applications—from healthcare using data science to personalized recommendations in patient care and drug development to Spotify using music data—data professionals of all stripes are on the rise. are in demand. And there are different job opportunities that cater to different interests and interests
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Data science careers command high salaries because there is not enough supply (professionals have about 20,000 open positions in the U.S., according to U.S. News) and their skills are in high demand.
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Data scientists are seeing this demand as more organizations have begun to see the importance of data-driven decision making over the past few years. Whether it’s e-commerce companies embracing artificial intelligence or travel companies incorporating machine learning into their platforms, data scientists are at the forefront of the latest technological revolution.
In the United States, data science professionals typically earn about $117,000 per year, according to Glassdoor. However, it depends on a number of factors, including years of experience, education level, industry, location, and area of expertise. For example, data scientists in big cities like New York or San Francisco can earn $180,000. Work for a government agency, nonprofit or health care organization
Responsibilities of data scientists may vary from company to company Generally speaking, data scientists source and process data available to the company.
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According to Glassdoor, the average annual salary for a data scientist in the United States is around $117,000.
Data engineers create pipelines that flow data from various sources. They focus on elements such as production preparation and raw data formatting, stability, scaling, data storage and security.
According to Glassdoor, the average annual salary for a data engineer in the United States is around $113,000.
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Information architects visualize and design an organization’s information management framework. They do this by assessing the organization’s information resources, then developing a plan to integrate, centralize, and manage the collected information.
– Application server software such as Oracle, user interface and GB software such as IBM DB2, and database management software such as Microsoft SQL Server.
According to Glassdoor, the average annual salary for a data architect in the United States is around $152,000.
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Data modelers translate real-world business needs into data models. They work closely with data architects to create conceptual, logical, and physical data models. They support the application team when designing the database and collaborate with the data governance team for compliance
According to Glassdoor, the average annual salary for a data modeler in the United States is around $106,000.
Big data engineering focuses on the infrastructure that allows people to collect and organize large amounts of data that make it usable for billions of clicks, taps, likes, swipes, shares and data analytics. They do this by focusing on data pipeline construction, data infrastructure design and management, data warehouse management, and ETL (extract, transfer, load) processes.
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According to Glassdoor, the average annual salary for a big data engineer in the United States is around $125,000.
A machine learning (ML) engineer is a programmer who designs self-driving software that uses data and automates predictive models. ML engineers bridge the gap between data and software, creating programs that allow machines to perform tasks without direct human assistance.
According to Glassdoor, the average annual salary for a machine learning engineer in the United States is around $123,000.
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Machine learning is a subset of data science.Although machine learning engineers and AI engineers do similar work, artificial intelligence (AI) engineering focuses more on developing systems and machines that mimic human cognitive functions. does, making them more adept at solving problems.
According to Glassdoor, the average annual salary for an AI engineer in the United States is around $118,000.
An enterprise architect is an IT professional who oversees an organization’s networks and services. They update systems throughout the company, replace hardware or software, and determine which products and services are the best support teams in an organization.
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According to Glassdoor, the average annual salary for an enterprise architect in the United States is about $164,000.
Business intelligence (BI) analysts use their data to make decisions. They collaborate with business teams to understand their needs, review data, and write financial and market intelligence reports.
Natural language processing engineers build systems and tools that can understand human language.A subset of artificial intelligence and machine learning, NLP engineers work at the intersection of computer science, information science, AI, and linguistics.
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According to Glassdoor, the average annual salary for an NLP engineer in the United States is $88,000.
Database administrators are often confused with database administrators, but their roles are different. The database manager maintains the functionality and functionality of the database while creating, updating and deleting the old database. Database administrators also maintain the security and safety of an organization’s database
According to Glassdoor, the average annual salary for a database administrator in the United States is around $76,000.
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According to Glassdoor, the average annual salary for a database developer in the United States is $97,000.
A stepping stone to a data science career, data analysts identify trends, patterns and relationships in data to inform business decisions. Data analysts mine data, curate insights, create visualizations, and present reports to stakeholders.
– Cleans data to get rid of false and inconsistent data, and gathers valuable insights by identifying patterns, relationships and trends.
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– Familiarity with data analysis tools such as Tableau, Google Analytics, Jupiter, Amazon Web Services and Microsoft Excel.
According to Glassdoor, the average annual salary for a data analyst in the United States is around $74,000.
The more a company relies on data, the more it pays its data scientists. Some of the highest paid data science firms are social networking sites (which collect user data), e-commerce platforms (which track customer behavior with billions of data points) and real-time services (which rely on data (does) are responsive to customers. .)
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Amazon’s data scientists work across all of its verticals, from analyzing customer purchase data on its e-commerce platform to analyzing user behavior for its advertising division.
The average salary for an Amazon data scientist is about $137,000, according to Glassdoor, although Amazon employees often earn more. In 2022, Amazon raised the salary threshold for corporate and technical employees to $350,000, citing competition for technical talent.
Uber data scientists work in product analytics (e.g. ensuring the accuracy of mapping and geolocation technology), finance and operations (e.g. helping the company with its financial planning and competitive strategy). data usage), and marketing (e.g. analytics to help shape insights). (Growth growth, brand awareness, customer retention, and engagement).
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Meta data scientists work on products such as Facebook, Instagram, Oculus, Messenger and WhatsApp. A data scientist focused on Instagram can drive a long-term strategy for revenue sharing with this democratizing department. A business analyst at WhatsApp may collaborate with sales and marketing teams to identify user growth opportunities. And a machine learning engineer at Facebook might work on fraud detection technology
According to Glassdoor, the average salary for a data scientist in Meta is around $152,000. As one of the world’s highest-paid technology companies, it’s not uncommon for data science professionals to earn more than $200,000 in meta.
From fraud prevention to helping determine rental rates, Airbnb data scientists work on a variety of products and features. As the company grows, so does the demand for data science experts Airbnb currently has a number of open roles for data scientists, machine learning engineers and analysts.
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Apple is a data collection juggernaut with more than 900 million active iPhones worldwide The company’s data science experts work in all its divisions including hardware, software, music and entertainment services.
Data scientists working for Booz Allen Consulting face a variety of clients and challenges, from helping commercial clients to military clients improve their cybersecurity.
Microsoft’s size, reach and product diversity mean its data scientists are tackling a variety of problems, from improving the Microsoft cloud to disrupting its language technology.
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According to O’Reilly’s Data Science Survey, the number of tools that data science professionals use can affect their compensation. Some salary-enhancing tools include Apache Spark, Scala, and D3, which can add more than $15,000 to a compensation package. Familiarity with cloud computing will also increase pay, with survey respondents who use Amazon Elasticsearch earning about $6,000 more.
O’Reilly also noted that someone who uses 10 or 14 can earn $30,000 more than someone who uses 15 or more devices.
Where you choose to work can determine your salary
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