Find the Best Jobs in Technology & Data

Don't miss out! Apply to real jobs posted by real employers on our award-winning platform.

Job Seekers

Post your resume on the best tech job board and apply to Tech Jobs, Analytics Jobs, and Data Jobs.
Add Resume

Employers

Advertise on the best tech job board to reach top talent for Tech Jobs, Analytics Jobs, and Data Jobs.
Post a Job

Latest Insights

Artificial intelligence (AI) has an apparent impact in our everyday lives. Nearly every critical sector or industry relies on AI to perform specific tasks that are difficult for humans to complete. This technology is revolutionizing how everyday world works which includes applications from streamlining operations to informing better decision making. By using this technology companies in all sectors are optimizing and automating their processes to increase profitability. Major drivers Major drivers for the market are growing big data, the increasing adoption of cloud-based applications and services, and an increase in demand for intelligent virtual assistants. However, a significant restraint to this market is the limited number of AI technology experts. "Critical challenges facing the AI market include concerns regarding data privacy and the unreliability of AI algorithms. Underlying opportunities in the artificial intelligence market include improving operational efficiency in the manufacturing industry and the adoption of AI to improve customer service," said Sachin Garg, Associate Vice President of  MarketsandMarkets, a global B2B research firm. According to a report from the firm, the artificial intelligence market is expected to reach USD $190 Billion by 2025, growing at a CAGR of 36% between 2018 and 2025. Artificial intelligence is also driving the market for semiconductor industry as AI chipsets have been the key enabler for this market. Processor, memory, and network have to be ready for such huge data analytics. Major industries Here are 10 major industries using different AI applications where the market is expected to have a significant impact for 2020 and beyond. 1. Healthcare The AI market for healthcare is used in various applications, such as patient data and risk analysis, medical imaging and diagnostics, precision medicine, lifestyle management and monitoring, drug discovery, inpatient care and hospital management, virtual assistants, wearables, and research. In addition, the increasing adoption of Electronic Medical Records (EMRs) and various advantages, such as predictive analytics and risk management, offered by AI systems to healthcare providers and payers are supporting the growth of the patient data and risk analysis segment. 2. Manufacturing The AI market for manufacturing is classified into various applications, such as material movement, predictive maintenance and machinery inspection, production planning, field services, reclamation, and quality control. Increasing demand to reduce operational costs caused by early-life failure of machines is driving the growth of predictive maintenance and machinery inspection in the AI market. 3. Automotive Machine learning (ML), natural language processing (NLP), and image processing are the leading AI technologies that are used in automotive sector. The automotive AI market is divided into multiple applications, such as autonomous driving, human-machine interface (HMI), and semiautonomous driving. Moreover, intelligent car initiatives, which give users an experience of advanced technology with effective vehicle controls such as advanced cruise control and self-parking, are further elevating the growth of HMI in the AI market. 4. Agriculture AI provides the status of crop water, along with soil water holding capacity. ML technology, along with computer vision technology, is a key element in the field of agriculture. The combination of IoT and advanced analytics with AI further allows farmers to analyze real-time data of weather conditions, temperature, soil moisture, plant health, and crop prices in the AI in agriculture market. Other applications include smart greenhouse management, soil management, and fish farming management. 5. Retail AI is extensively used in the retail sector to make the shopping experience similar to what the customers are accustomed to in real life. In the retail AI market, various applications are product recommendation and planning, customer relationship management, visual search, virtual assistants, price optimization, payment services management, supply chain management, demand planning, and others (website and content optimization, space planning, fraud detection, and franchise management). 6. Security The cybersecurity ecosystem is rapidly changing as new types of cyberattacks are constantly being found, and organizations have to keep up with these threats to protect their critical assets. The AI market for security have multiple applications, such as identity and access management (IAM), risk and compliance management, encryption, data loss prevention (DLP), unified threat management (UTM), antivirus/antimalware, intrusion detection/prevention system (IDS/IPS), and others. 7. Human Resources AI is reshaping the way companies manage their HR pools, policies, and practices. AI applications used in the HR sector are virtual assistants, personalized learning and development, applicant tracking and assessment, HR analytics, job recommendation, and sentiment analysis. 8. Marketing AI in the field of marketing is one of the largest and substantial  applications, mainly for media and advertising purposes. Analytics, consumer behavior prediction, digital assistants, and automation are the main applications of AI in advertising. AI helps identify the relevance, whether it refers to personalizing online content and other recommendations or to targeted advertising. 9. Law AI technologies, especially ML and NLP, are being deployed to increase productivity, improve margins, and provide innovative and efficient legal advice. Some of the biggest applications of AI in the law sector are eDiscovery, legal research, contract analysis, case prediction, compliance, and others (intellectual property, e-billing, and knowledge management). It is even predicted to employ AI robots for such advisory and legal processed in the future. 10. FinTech AI in fintech refers to the theory and development of computer systems capable of performing finance-related tasks that usually require human intelligence. Various applications of AI in fintech are business analytics and reporting, customer behavior analytics, market research, and capital optimization, among others. Moreover, virtual assistants and chatbots are widely used by financial institutions as they are changing the way banks interact with their customers. Overall, it depends on what type of AI Infrastructure have you adopted for your company. Read on For more information, read the full report by MarketsandMarkets, titled Artificial Intelligence Market - Global Forecast to 2025 . In addition to historical trends and forecasts, the report highlights some key players in the AI market, including the following: Intel (US) NVIDIA (US) Samsung Electronics (South Korea) Xilinx (US) Micron Technology (US) IBM (US) Microsoft (US) Google (US) Amazon Web Services (US) Facebook (US) Oracle (US) Cisco (US) Siemens (Germany) Article published by icrunchdata Image credit by Getty Images, Moment, Andriy Onufriyenko Want more? For Job Seekers | For Employers | For Influencers
A combination of megatrends, market demand, and new innovations has thrust many technologies into the spotlight. These tech innovations are likely to have the greatest impact during the next 10 years, according to Lux Research in its annual report titled "20 for 2020". The new report combines the power of insights from technology experts with proprietary data science tools to better guide innovation decision making. Below is a ranking of 20 technologies that will reshape the world, based on innovation interest scores from the Lux Intelligence Engine, along with input from Lux's leading analysts. It provides data-backed context for the ever-shifting technology landscape and insights into how companies can maximize the investment opportunities these data trends reveal. The 20 technologies are: 1. 5G Networks From robotic surgery to self-driving cars, 5G will be critical to advances in the internet of things. 5G has officially left the realm of research and entered reality, with more than 2,200 patents being filed this year. 2. Shared Mobility With more than $10 billion in funding every year for the past three years, shared mobility – like car-sharing services – are reinventing urban transportation. 3. Advanced Plastic Recycling Mission-critical for companies from CPGs to chemicals, China has invested in recycling technology in a big way, with 55% of all patents coming from that country. 4. Solid-State Batteries Incumbent Li-ion batteries are hitting a performance plateau, and with more than 500 patents filed last year, solid-state battery production is quickly becoming less theoretical. 5. Protein Production Next-generation protein are needed to feed a population of almost 10 billion and received five times the investment of the previous year, landing at more than $200 million. 6. Commercial Vehicle Automation Improvements in operator efficiency and safety will lower operation costs. 7. Point-of-Use Sensing Individualized, real-time data enables new business models for B2B and B2C alike. 8. 3D Printing Increasingly being used to manufacture production parts. 9. Energy Trading Platforms Threaten to disrupt conventional electricity retail. 10. Natural Language Processing Scalable solution to reduce repetitive tasks and improve efficiency. 11. Hydrogen and Fuel Cells Will be integral for growing renewables and decarbonizing industry. 12. Materials Informatics Can dramatically speed development time for materials and formulations. 13. Quantum Computing Addresses problems that are unsolvable by conventional computers. 14. Last-Mile Delivery Mobility is shifting to incorporate new modes of last-mile transport. 15. Blockchain A tool for establishing trust where regular databases can't. 16. Battery Fast Charging Infrastructure to quickly add range is becoming a need-to-have. 17. Omics Biological digital twins can address key challenges in medicine, materials, and agriculture. 18. 2D Materials Graphene is displacing conventional materials from composites to electronics. 19. Flow Batteries Offer support to daily wind and solar fluctuations without relying on natural gas. 20. Vertical Farming Meets consumer demand for local produce using less water, pesticides, and energy. Evolving landscape 5G networks claim the top spot in the report, 12 spots over the previous year's report. In fact, 11 of the 20 technologies on this list did not even appear on the previous year's list, and six of the nine returning technologies moved up in ranking. "One of the most exciting trends this list highlights is how rapidly the tech innovation landscape is evolving," said Michael Holman, Ph.D., Vice President of Research at Lux. "The number of newcomers on the list, along with progress in returning technologies, shows how rapidly innovation is progressing, creating compelling new growth opportunities as well as disruptive threats to incumbents." Missing from the list Nine technologies that made the cut in 2019 but were absent from this year's list are listed below. They can be broken down into three categories: Went Mainstream: 1. Machine learning 2. Cybersecurity  3. Microbiome Changed Form: 4. Wearable technology 5. Genome editing 6. Precision medicine Fell, in Relative Terms: 7. AR/VR; Drones 8. Perovskite solar 9. Generative design To see the full "20 for 20" list and to learn more about how these technologies have the potential to significantly impact investment into new technologies, you can download the report's executive summary . Article published by icrunchdata Image credit by Getty Images, DigitalVision Vectors, mathisworks Want more? For Job Seekers | For Employers | For Influencers
When it comes to presenting in front of high-level decision-makers within an organization, data, analytics, and objective insights are king. The problem is that communicating this information is challenging. Mandel, a provider of communication skills training for professionals, has four tips for business managers, sales teams, and technical or analytical professionals to help them deliver powerful data-backed presentations when presenting data and analytics. Better Presentation Skills While there are exceptions to the rule, most people are prone to doze off and fall asleep when presented with cold, hard facts. Yet, if someone is presenting something of value to decision-makers within the organization, data is their best friend. It's objective and irrefutable. Thus, in order to maximize the value of data without tranquilizing an audience with a heavy dosage of boredom, presenters have to find a way to make their presentations engaging. Here are some suggestions: 1. Use the Right Software Raw data is basically useless in a presentation setting. While speakers can use it to generate findings and reach conclusions, the audience isn't going to follow them step by step through the discovery process. They want data delivered on a silver platter – already clean, refined, and ready for consumption. The best way to show them the findings without oversimplifying or overcomplicating is to use data visualization and analytics software. 2. Structure Presentations Properly How speakers structure their presentations will, to a large degree, determine its influence. Know the audience and choose a structure that's conducive to smooth mental processing. Many speakers find the rule of three to be ideal when delivering data-based presentations. "Humans are both neurologically and culturally adapted to the number three and its combination of brevity and rhythm," founder Steve Mandel explains. "We know from studies in neuroscience that our brains seek out patterns and find the structure of three to be a complete set; it feels whole," said Mandel. There are multiple ways to follow the rule of three, but it typically involves: Raising a problem or opportunity to grab attention; Suggesting how a problem can be resolved; and Sharing a tightly focused agenda that reconciles the problem and provides direction. 3. Leverage Visual Storytelling There's a time and place for dishing out statistics in a spreadsheet, but speakers are almost always better off leveraging visual storytelling. Colorful charts with simple legends and clear takeaways – coupled with real-world illustrations that exemplify the findings – are the way to go. 4. Summarize Findings At the end of the presentation, audibly recap what was covered by synthesizing the data into a couple of key points. Provide a handout at the end of the presentation that lists the key data points on a single sheet of paper. After the presentation is over, these are the takeaways the audience will remember. Article published by icrunchdata Image credit by Mandel Communications Want more? For Job Seekers | For Employers | For Influencers  
View All Insights