Here is a curated list of the top recession-proof data science companies to keep an eye on in 2023
Data science is changing many different businesses. It’s hardly surprising that demand for data scientists is rising rapidly given how useful insights gained from data are enabling data science companies to make more informed decisions. It is estimated that job opportunities for data science roles will grow 22% by 2030.
The top data science companies to work for are listed below. Data science is the study of data with the objective of getting significant business insights. It combines concepts and methods from the fields of mathematics, statistics, artificial intelligence, and computer engineering to analyze enormous amounts of data. No matter their size, recession-proof data science companies must have a robust data science strategy if they want to grow and keep a competitive edge against other data science companies. In this article, we discuss some of the recession-proof data science companies to follow in 2023 that’ll help you in the future.
EY is a multinational accounting and professional services corporation with expertise in corporate finance, strategy, consulting, and transactions. EY leverages data and artificial intelligence to re-engineer processes, improve risk controls, and provide its customers with a competitive edge. To create new revenue possibilities, manage performance, and drive capital allocation plans, analytics and AI are integrated into their business operations.
VMware is a corporation that creates virtualization and cloud computing technology solutions for multi-cloud enterprises. The development of anomaly detection, cryptographic agility, cache-adaptive algorithms, and CloudCast at VMware is driven by data science.
In addition to developing fresh and creative ways to use various types of data, Walmart is dedicated to analyzing a tonne of already-existing data. Walmart uses extensive data mining to identify point-of-sale data trends that are subsequently used to supply chain optimization, product assortment optimization, and retail checkout improvements.
Data is used by PwC, a global network of professional services businesses, to measure market size, determine risk premiums, and enhance its Total Impact Measurement and Management (TIMM) framework. Additionally, it provides extensive, adaptable, and competitive pay and benefits.
Splunk is the first data-to-everything central platform in the world, enabling users to search, monitor, and analyze their data. Advanced built-ins including outlier identification, predictive analytics, event grouping, and forecasting are used by users as they engage with a web-style interface. These products support organizations in improving their cloud transition, resilience, and digital customer experience.
For e-commerce, the numerator emphasizes consumer insights. Numerous Fortune 100 organizations use Numerator, and its data scientists assess buying environments, feelings, behaviors, and outcomes using client and customer data.
A relatively new business, Databricks has its roots in academia and the open-source community. The Lakehouse Platform, an open and integrated platform for data and AI that combines the finest features of data warehouses and data lakes, is the company’s main offering. Shell, HSBC, T-Mobile, and the H&M Group are just a few of the biggest companies in the world that depend on Databricks to allow massive-scale data engineering, business analytics, full-lifecycle machine learning, and collaborative data science.
A hybrid data cloud business called Cloudera makes data and analytics simple and available to everyone. Private and public clouds can be combined by clients to uncover more potent business insights. A wide range of sectors, including financial services, retail, technology, healthcare, education, and manufacturing, are served by Cloudera.
Machine learning model deployment and administration solutions are offered by Algorithmia. It makes use of top-tier enterprise-grade infrastructure, which DataRobot just purchased, to manage the production machine learning lifecycle inside already-in-place operational procedures. To operationalize their machine learning use cases, thousands of non-governmental organizations, government intelligence agencies, and Fortune 500 firms use Algorithmia.
Cropin is an AgTech company that enables data-driven farming using Earth observation and AI. Using a multidisciplinary approach toward AI, earth observation, agriculture, meteorology, and computer sciences, it seeks to “re-imagine agriculture with data.” Cropin uses pixel-level information from satellite photography to provide useful knowledge and enhance the agricultural environment. In more than 50 countries, Cropin currently offers SaaS solutions to 225 agribusinesses as well as numerous governmental and non-governmental organizations.
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