Best Companies for Data Scientists in 2023: Top-tier Titans
This compilation of the finest data science companies seeks to extend beyond the usual suspects, presenting exceptional and possibly overlooked opportunities for aspiring data scientists.
Since the 1960s, the concept of big data has taken root and flourished worldwide. According to Oracle, big data refers to information that “contains greater variety, arrives in increasing volumes, and has more velocity.” This evolution has led to the emergence of vast, intricate datasets that offer insights into an even wider range of business challenges.
As a result, data science companies have sprung up across various industries, dedicated to scrutinizing this data for invaluable business intelligence.
This surge in business prospects directly translates into an array of job opportunities. While only a handful of universities offer dedicated data science programs, the industry is experiencing exponential growth. A plethora of data science companies have surfaced, and virtually every major organization has a team of data scientists on board.
As per Bernhardt Schroeder’s report in Forbes, the data science sector in the U.S. is projected to grow by 28% by 2026, resulting in a multitude of vacant positions for data scientists. Therefore, if you possess the requisite skills and interest, the options are virtually limitless. Which data science companies stand out as the best, and how do you determine which one aligns best with your aspirations?
When one contemplates becoming a data scientist, popular choices like Google and Facebook often spring to mind. While we have extensively covered data science roles at these tech giants in our Ultimate Guide to the FAANG Companies, this list is designed to venture beyond the conventional and anticipated options. Its purpose is to present exceptional and potentially underestimated avenues for aspiring data scientists.
♦ Qualities of a Superlative Data Science Company
In the quest for the premier data science company to work for, numerous factors come into play. Individual preferences may lead you towards smaller data science companies, or perhaps those operating within a specific industry. Additionally, geographical considerations might play a role.
While some may gravitate towards customer-centric enterprises that afford ample opportunities to explore personal data science interests, others may have entirely different priorities.
In this guide, we will navigate through what I deem to be the most outstanding companies for data scientists, factoring in compensation, work-life balance, industry influence, and the inherent coolness factor. Lastly, I have categorized them by company size for your convenience.
“Without further delay, let’s explore the very best of data science companies”.
Microsoft boasts a myriad of captivating data science projects and products. While renowned as an enterprise and consumer software company, Microsoft also commands a significant presence in the tech realm, making it a formidable data science entity. For instance, their project “AI for Earth” empowers environmental conservationists by putting cloud and AI tools in their hands.
Microsoft’s dedication to sustainability is further evident in their development of open-source tools, data, APIs, and models. Their “AI for Accessibility” program endeavors to bridge gaps in AI datasets, particularly for individuals with disabilities.
In addition to their commendable research and open-source initiatives, Microsoft offers an extensive range of products for consumers, enterprises, and developers. From Microsoft Word to Xbox, the spectrum is vast. With such diverse end users and product offerings, you are bound to discover an area that aligns with your interests.
The abundance of data, analytics, and AI positions worldwide further solidifies Microsoft’s standing as one of the premier data science companies. The array of teams with distinct needs and projects makes it fertile ground for diverse opportunities. Feel free to explore and identify a product area or team that resonates with you.
If the prospect of embarking on a data science journey with Microsoft piques your interest, I encourage you to peruse our comprehensive guide on securing a data scientist role at Microsoft.
Amazon’s evolution from an online bookstore to a multifaceted technological powerhouse is a testament to its adaptability and innovation. As a data scientist, Amazon presents an exceptional workplace.
Amazon Web Services (AWS) commands the largest market share in the cloud services industry, solidifying its position as a dominant force in the realm of data science companies.
In addition to its AWS-centric data science services, Amazon leverages machine learning to detect and combat fraud among its extensive array of transactions.
Given the sheer volume of data generated and collected by Amazon’s eCommerce business, there is a wealth of intriguing and informative data at the company’s disposal. The prospect of delving into this data is undoubtedly enticing for data scientists.
Amazon offers an abundance of data science positions, ranging from supply chain optimization to demand forecasting. The range of compelling challenges awaiting data scientists at Amazon is truly remarkable.
Airbnb has demonstrated a profound commitment to revolutionizing the travel industry, and data scientists play a pivotal role in this transformation. Their former head of data science aptly described Airbnb’s approach: “We look at data as the voice of the customer, and data science as the interpretation of that voice.”
For those inclined towards customer-centric enterprises, Airbnb stands as an exemplary workplace. Every decision made at Airbnb is guided by a purpose and logic that ultimately benefit both the customer and the business.
Airbnb leverages data science to enhance various facets of its services, including search and hiring practices. The company’s culture places a premium on self-reflection and constructive criticism, fostering an environment conducive to growth. Airbnb also offers a diverse array of data science positions in finance, trust, and guest experiences.
With such a broad spectrum of focus areas, data scientists at Airbnb have the opportunity to explore various industries and expand their horizons. This diversity of experience positions Airbnb as one of the finest data science companies to work for.
Nvidia is in a class by itself when it comes to data science firms. The company pioneered “accelerated analytics,” which processes data up to 20 times quicker without the need for refactoring. This achievement was made possible by the use of GPUs, specifically the NVIDIA DGX A100s. Time is money in business, and Nvidia’s breakthroughs in graphics cards have translated into significant success.
Data scientists at Nvidia have the potential to improve the work of their peers throughout the world. The opportunity for data scientists to increase the efficiency of their work is enormous, making Nvidia an unrivaled choice for impact-driven professionals.
The company also provides data science consulting services to clients, leveraging data science to optimize the popularity of their products. With a plethora of open data science positions, ranging from data architects to data generation engineers, Nvidia offers a wealth of opportunities for data scientists to thrive.
Oracle’s cloud platform is a technological marvel that empowers users to harness the potential of their data through machine learning models, visualizations, and predictive analytics. As a data scientist contributing to the development of this platform, you have the privilege of creating a suite of exceptional models and tools for end users to apply to their data.
The analytics platform is equipped with “embedded machine learning and natural language processing technologies [that] help increase productivity.” This endeavor presents an immense opportunity to enhance the quality of life for Oracle’s customers.
Data scientists at Oracle can engage in a diverse range of projects, spanning from advertising and product design to the organization and analysis of unstructured data.
With thousands of open data science positions available across various internal departments, Oracle is an outstanding choice for data scientists seeking to diversify their experience and reputation.
Delta, headquartered in Atlanta, may not be the first airline that comes to mind when contemplating data science companies. However, Delta has made substantial strides in applying machine learning to decision science, achieving feats unparalleled in the airline industry.
Leveraging its extensive historical data, data scientists at Delta simulate operational challenges to devise solutions that minimize customer impact. This data-driven approach represents a refreshing departure from conventional practices, as Delta harnesses the power of data to optimize the customer experience.
As the principal airline at Hartsfield-Jackson International Airport, the world’s busiest airport, efficiency and optimization are paramount objectives for Delta. The company offers a plethora of open data science roles, with the majority of them based in Atlanta, Georgia.
Delta stands as one of the finest data science companies to work for in the Southeast. Data scientists at Delta have the opportunity to tackle a wide range of focus areas, from health analytics to operations decision science. This diversity of projects ensures that data scientists at Delta are constantly engaged in solving captivating challenges.
Splunk’s central data platform is designed to enable users to monitor, investigate, analyze, and take action on their data securely, resulting in more efficient operations. With built-in machine learning capabilities including outlier detection, forecasting, event clustering, and predictive analytics, Splunk is an excellent fit for data scientists passionate about hardcore machine learning models.
The platform facilitates data streaming across multi-cloud environments, providing real-time search capabilities for both structured and unstructured data. If you have a penchant for delving into complex machine learning models, Splunk is an ideal destination for you.
Branded as the “hybrid cloud company,” Cloudera empowers customers to seamlessly blend private and public clouds. This enables the amalgamation of internal and external data, generating more potent insights for the end user.
Cloudera stands out among data science companies due to its robust and scalable cloud data platform. The Cloudera Data Platform (CDP) hybrid cloud operates where the client’s data resides, resulting in enhanced speed and security.
Data scientists at Cloudera are primarily focused on data management and the company’s machine learning platform, making it an excellent choice for those interested in these domains.
Numerator is a leading data science company dedicated to providing customer insights for eCommerce. Their mission is to offer insights “to help you market to consumers, not demographics.” Numerator places a premium on the ease of implementation of its product, boasting a rapid deployment timeline.
As the largest and most diverse consumer purchase panel, Numerator generates a wealth of data, which is meticulously analyzed to provide valuable insights to its customers. The company fosters an environment that empowers data scientists to drive projects from conceptualization to production. If you thrive on unstructured work with open-ended questions, Numerator is among the top data science companies to consider.
Much like Cloudera, Teradata operates as a hybrid cloud platform, facilitating the integration of public clouds (such as Azure and AWS) with on-premise solutions. Similar to many other data science companies, Teradata also provides consulting services to enterprise customers, aiding them in maximizing the benefits of their solutions.
Teradata’s flagship product, Vantage, is a software suite encompassing integrated analytics functions that can be executed across multiple platforms, delivering insights at scale. Data scientists at Teradata have the opportunity to enhance and expand the analytics functions provided, including machine learning, statistical analysis, text processing, and more.
The company places great emphasis on academic rigor, encouraging activities such as patent filing, journal publication, and conference participation. If you’re passionate about merging data expertise with algorithmic knowledge, Teradata offers an exceptional community and networking opportunities for data scientists.
Databricks’ Lakehouse platform combines the best of data lakes and data warehouses, offering a cost-effective solution that combines the advantages of both approaches. The platform aims to eliminate data silos, enabling seamless integration of analytics, data science, and machine learning. Built on top of open-source platforms, the Lakehouse maximizes usability and flexibility.
Databricks’ open data scientist positions present substantial opportunities for impact, as responsibilities encompass shaping the direction of data science solutions, including tasks such as forecasting, product analysis, churn prediction, and insight generation.
Data scientists at Databricks also have the opportunity to represent their field at a company-wide level, promoting a data-driven mentality. Positions range from data solutions architects to machine learning platform engineers, providing a diverse array of opportunities for data scientists.
With a legacy of innovation in technology, IBM continues to be a powerhouse in the field of AI and machine learning. Data scientists at IBM have the opportunity to work on cutting-edge projects that span industries and have a global impact. The company’s commitment to pushing the boundaries of what’s possible in AI makes it an exciting workplace for data scientists. By joining IBM, you’ll be part of a team that is shaping the future of artificial intelligence and machine learning.
Uber’s data-centric approach has revolutionized the transportation industry. Data scientists at Uber work on a wide range of challenges, from optimizing ride routes to enhancing driver-partner experiences. The wealth of data generated by Uber’s platform provides fertile ground for data scientists to make meaningful contributions. By joining Uber, you’ll be at the forefront of transportation optimization, influencing how millions of people move around their cities.
As a leader in the entertainment industry, Netflix relies heavily on data science to understand viewer preferences and deliver personalized content recommendations. Data scientists at Netflix play a pivotal role in shaping the future of entertainment, using their expertise to drive content creation and distribution strategies. Joining Netflix means being part of a team that is redefining how entertainment is delivered to millions of viewers around the world.
Apple’s commitment to privacy is legendary, and this ethos extends to their approach to data science. Here, data scientists work on cutting-edge projects while ensuring the utmost respect for user privacy. Apple’s focus on creating meaningful, privacy-conscious experiences sets it apart as an ideal workplace for data scientists who value ethical data handling. By joining Apple, you’ll be part of a team dedicated to pushing the boundaries of technology while respecting user privacy.
At Facebook Meta, data scientists have the opportunity to delve into one of the most extensive repositories of social data in the world. This presents a unique opportunity to influence the way people connect and interact online. From user behavior analysis to content personalization, the impact of data science at Facebook Meta is immense. Joining this team means being at the forefront of social data analysis and contributing to the future of online interactions.
Salesforce empowers businesses with powerful CRM solutions, and data science plays a central role in this endeavor. Data scientists at Salesforce work on projects that directly impact how businesses engage with their customers. The platform’s extensive ecosystem provides a wealth of opportunities for data scientists to drive meaningful change. Joining Salesforce means being part of a team that is revolutionizing how businesses interact with their customers and shaping the future of customer relationship management.
Palantir’s mission is to solve the world’s most pressing problems through data-driven solutions. Data scientists at Palantir work on projects with far-reaching implications, from national security to public health. The opportunity to apply data science in such critical domains makes Palantir an exceptional workplace for those seeking to make a profound impact. By joining Palantir, you’ll be part of a team that is using data-driven insights to address some of the most challenging issues facing society today.
The landscape of companies employing data scientists is vast and diverse. Data science roles may entail working on proprietary platforms for machine learning or data science or applying data science principles within specific industries. The best fit for you ultimately hinges on your personal interests and career aspirations.
If you possess a profound passion for environmental conservation, a role like AI for Earth at Microsoft may be the perfect fit. Conversely, if you’re deeply passionate about pure data and intrigued by the eCommerce sector, Numerator could be an excellent match.
“The abundance of choices is a blessing. If you haven’t pursued formal education in computer science or data science, it may be advantageous to seek out data science positions within your existing industry. Your contextual knowledge can provide a unique advantage over other data scientists who may lack familiarity with your industry.”
A standout data science company is characterized by several factors, including the potential for growth, industry focus, and geographic considerations. Personal preferences may lead one to prefer smaller companies, specific industries, or certain geographic locations.
What Are Some Noteworthy Data Science Companies?
Noteworthy data science companies include Microsoft, Amazon, Airbnb, Nvidia, Oracle, Delta, Splunk, Cloudera, Numerator, Teradata, and Databricks. Each company offers unique opportunities for data scientists based on their areas of expertise and focus.
When selecting the right data science company, consider factors such as your personal preferences, career aspirations, and the company’s industry focus. Additionally, assess aspects like compensation, work-life balance, and industry significance.
What Are Some Medium and Small Data Science Companies Worth Considering?
Medium and small data science companies worth considering include Splunk, Cloudera, Numerator, Teradata, and Databricks. These companies offer distinct opportunities for data scientists and are known for their innovative approaches to data science.
Should I pursue formal education in data science to excel in the field?
While formal education in data science is valuable, it’s not the only path to success. Many data scientists have excelled in the field through self-guided learning, practical experience, and leveraging their existing industry knowledge.
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