Business Strategy Analyst Salary – Data science is a field that spans several different disciplines. But all of these data science roles require strong analytical skills, technical knowledge, and the ability to extract actionable insights from reams of information.
As more and more industries use innovative data applications—from healthcare using data science to improve patient care and drug development to Spotify using music data for personalized recommendations—data professionals from all tapes are in high demand. And there are many different job opportunities that suit a wide range of passions and interests.
Business Strategy Analyst Salary
Data science occupations command high salaries because they are in short supply (the profession has nearly 20,000 open positions in the United States, according to US News) and their skills are in high demand.
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Data scientists are seeing this demand as, over the past few years, more and more organizations have begun to realize the importance of data-driven decision making. Whether it’s e-commerce companies dabbling in artificial intelligence or travel companies incorporating machine learning into their platforms, data scientists are at the forefront of the latest technology revolution.
In the United States, data science professionals typically earn about $117,000 per year, according to Glassdoor. However, this can vary based on several factors, including years of experience, education level, industry, location and area of specialization. For example, in big cities like New York or San Francisco, data scientists can earn up to $180,000. Machine learning engineers often earn more than data analysts, and those working in the consumer technology sector typically earn more than those working for government agencies, non-profit organizations or healthcare organizations.
Data Scientist responsibilities can vary from company to company. Generally speaking, data scientists collect and process data available to a company.
The average annual salary for a data scientist in the United States is about $117,000, according to Glassdoor.
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Data engineers build pipelines that bring data from various sources. They focus on raw data production readiness and elements such as formats, resiliency, scaling, data storage and security.
The average annual salary for a data engineer in the United States is about $113,000, according to Glassdoor.
Data architects visualize and design an organization’s data management framework. They do this by evaluating the organization’s data sources and then designing a plan to integrate, centralize, and maintain the collected data.
– Application server software such as Oracle, user interface and query software such as IBM DB2, and database management software such as Microsoft SQL Server
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The average annual salary for a data architect in the United States is about $152,000, according to Glassdoor.
The data modeler turns real-world business needs into data models. They work closely with data architects to create conceptual, logical, and physical data models. They support application teams in database design and collaborate with data management teams for compliance.
The average annual salary for a data modeler in the United States is about $106,000, according to Glassdoor.
Big data engineering focuses on the infrastructure that enables people to collect and organize massive amounts of data. This makes billions of clicks, taps, likes, swipes, shares and purchases usable for data analysis. They do this by building data pipelines, designing and managing data infrastructures, handling data storage, and focusing on the ETL (Extract, Transform, Load) process.
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The average annual salary for a big data engineer in the United States is about $125,000, according to Glassdoor.
A machine learning (ML) engineer is a developer who designs standalone software that uses data and automates predictive models. ML engineers bridge the gap between data and software, creating programs that allow machines to function without direct human assistance.
The average annual salary for a machine learning engineer in the United States is about $123,000, according to Glassdoor.
Machine learning is a part of data science. Although machine learning engineers and AI engineers perform some of the same tasks, artificial intelligence (AI) engineering places more emphasis on developing systems and machines that mimic human cognitive function, making them more adept at solving of problems.
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The average annual salary for an artificial intelligence engineer in the United States is about $118,000, according to Glassdoor.
An enterprise architect is an IT professional who oversees an organization’s networks and services. They update company-wide systems, replace hardware or software, and determine which products and services are best supported by support teams within the organization.
The average annual salary for enterprise architects in the United States is about $164,000, according to Glassdoor.
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.
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Natural language processing engineers build systems and devices that understand human language. A subset of artificial intelligence and machine learning, NLP engineers work at the intersection of computer science, information science, artificial intelligence, and linguistics.
The average annual salary for an NLP engineer in the United States is about $88,000, according to Glassdoor.
Database managers are often confused with database administrators, but their roles are different. While the former creates, updates and deletes databases, the database manager maintains the results and performance of the database. Database managers also maintain the safety and security of an organization’s databases.
The average annual salary for a database manager in the United States is about $76,000, according to Glassdoor.
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The average annual salary for a database developer in the United States is about $97,000, according to Glassdoor.
A stepping stone to a career in data science, data analysts identify trends, patterns and relationships in data to inform business decisions. Data analysts mine data, organize insightful discoveries, build visualizations and present reports to stakeholders.
– Data cleaning to free the data from errors and inconsistencies and to obtain valuable information by identifying patterns, relationships and trends
– Knowledge of data analysis tools such as Tableau, Google Analytics, Jupiter, Amazon Web Services and Microsoft Excel
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The average annual salary for a data analyst in the United States is about $74,000, according to Glassdoor.
The more a company relies on data, the more it pays its data scientists. Some of the highest-paid data science companies are social networking sites (which collect tons of user data), e-commerce platforms (which track billions of data points on user behavior), and real-time services (which depend on responsive customer data).
Amazon’s data scientists work across all its verticals, from analyzing consumer purchase data on the e-commerce platform to analyzing consumer behavior for the advertising department.
The average base salary for an Amazon data scientist is about $137,000, according to Glassdoor, although Amazon employees often earn much more. Amazon raised the base salary cap to $350,000 for corporate and technology employees in 2022, citing competition for tech talent.
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Uber’s data scientists work in product analytics (e.g. ensuring the accuracy of maps and geolocation technologies), finance and operations (e.g. using data to help the company with its financial planning and competitive strategy), and marketing (e.g. .relying on analytical insights to improve customer growth, brand awareness, retention and engagement).
Meta data scientists work on products like Facebook, Instagram, Oculus, Messenger and WhatsApp. A data scientist focused on Instagram can help its monetization department manage a long-term revenue sharing strategy. A Business Analyst at WhatsApp may collaborate with sales and marketing teams to identify opportunities for user growth. And a machine learning engineer at Facebook might work on fraud detection technology.
The average base salary for a data scientist at Meta is about $152,000, according to Glassdoor. As one of the highest paying tech companies in the world, it’s not uncommon for data science professionals to earn over $200,000 at Meta.
Airbnb’s data scientists work on a range of products and features, from fraud prevention to help with rental pricing. As a company grows, so does its demand for data science professionals. Airbnb currently has dozens of open positions for data scientists, machine learning engineers, and analysts.
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With more than 900 million active iPhones worldwide, Apple is big on data collection. The company’s data science experts work across all of its divisions, including hardware, software, music and entertainment services.
Data scientists working for consulting firm Booz Allen are exposed to a variety of clients and challenges, from helping commercial clients improve their cybersecurity to assisting military clients.
Microsoft’s size, scope and variety of products means its data scientists can solve a wide range of problems, from improving Microsoft’s cloud to preventing bias in its language technologies.
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The number of tools a data scientist has mastered can affect their compensation, according to O’Reilly’s Data Science Research. Some salary-boosting toolsets include Apache Spark, Scala, and D3, which can add more than $15,000 to a compensation package. Familiarity with cloud computing will also increase wages, with respondents using Amazon Elastic MapReduce receiving a salary increase of about $6,000.
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O’Reilly also noted that those who use 15 or more tools can earn up to $30,000 more than those who use only 10 to 14. There is a premium associated with mastering different tools.
Where you choose to work can determine your salary.