Chiebuka Christopher’s Post

Data engineering is a crucial role that’s in high demand today. Companies are looking for professionals who can build and maintain the infrastructure that supports analytics, AI, and machine learning. It’s not a fallback career; it’s a critical role driving innovation in today’s tech landscape. Like any career, passion is key. If you're not passionate about the field, it may not be for you—just like in software engineering, or any other career. Data engineering opens doors to cutting-edge opportunities in machine learning, AI, and data science. It offers not just a solid salary but also the chance to work on meaningful, impactful projects. So, if you're interested in working on the forefront of technology, data engineering is definitely a path worth considering. Hashtags: #DataEngineering #AI #MachineLearning #TechCareers #Innovation #CareerGrowth #TechIndustry #DataScience #Infrastructure #Analytics #FutureProof #PassionInTech #MeaningfulWork #CuttingEdgeTechnology #TechInfrastructure #CareerOpportunities

I realized that I have more than one full-time job... The time I spend on studying and trying to keep up to date in my field feels like another job. Challenging? Definitely. But I don't see another option. 15 years ago very few people knew about Data Science. Now, we have a full area split into Data Engineering, MLOps, Data Analytics, ML Engineering, AI Engineering, etc. Where would it be in 5, 10, 15 years? It will be different but I don't know how. At least, I can build my resilience by studying. How do you stay updated in your field? #motivation #datascience #personaldevelopment #education

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DVA is not associated with this job posting Staff Data Scientist at Correlation One https://lnkd.in/gFGbuM65 A Day In the Life: Architect and build scalable machine learning solutions and AI applications Design and implement reliable, reusable frameworks and abstractions to standardize AI model development. Engage in hands-on development, from model prototyping to deploying scalable AI systems. Lead efforts to ensure that AI models and data practices uphold ethical standards, including fairness, transparency, and accountability. Work closely with product managers and business stakeholders to translate business challenges into data-driven projects that deliver measurable outcomes. Mentor junior data scientists and foster a culture of technical excellence. Stay updated and educate the team on the latest trends in AI and machine learning technologies. #employeeexperience #people #culture #hiring #talent #skills #passion #leadership #hr #humanresources #team #strategy #hrstrategy #business #team #careers #employment #jobs #hiring #job #jobsearch #recruitment #career #work #careers #recruiting #nowhiring #resume #jobhunt #business #jobseekers #jobopening #jobseeker #hiringnow #interview #jobsearching #vacancy #cfbr #education #jobinterview #jobopportunity #employmentopportunities

Ready to embark on a thrilling career switch in 2024? Dive into the world of AI engineering, data science, analysis, and engineering! Unlock limitless opportunities in the realm of data-driven innovation. Let's shape the future together! #CareerSwitch #AI #DataScience #DataAnalysis #DataEngineering #NewBeginnings #dataanalyst #DataMites #aiengineer #datascientist

The average salary for a Deep Learning Engineer is $163654 per year in United States. Checkout this amazing Deep Learning and Neural Networks cheatsheet, it's worth a watch. Please reshare to your #LinkedIn network so everyone can take advantage of these resources! ➡Follow Shivam Modi (43K Followers) to get Data Science and Machine Learning material daily. PS. In just 5 months, You can become Job-Ready Data Scientist & Analyst. ➡Link: https://lnkd.in/dE9CUB2z Here's what you'll get: 1. Hands-on Practical Experience  2. 1:1 Doubt Clearance Sessions 3. Real-Time Capstone Projects No prior coding experience required, Limited Time Offer! #data #datascience #datascientist #machinelearning #dataanalytics #ai

☆☆☆☆☆☆ We're hiring data scientist ☆☆☆☆☆☆ Hot job opening 👉 https://lnkd.in/gup7Zx-a Elite in semiconductor industry work smart with methodology of targeted search instead of blanket search for speedy product verification and time to market. Calls for digital tool driven by quality mindset. We are professional design house startup from enterprise group, dedicated to GaN power devices for edge applications. Manage everything with matrix thinking to remove blindspot caused by one-way thinking. Purely data talk and free from any bias. Now we're recruiting young talent of data scientist for semiconductor device engineering. Let's embrace the upcoming era of smart design. Please join us with your shiny brain! #DataTalk #DataScientist #DataAnalyst #DataAnalytics #DataVisualization #DataViz #DataScience #DataBase #BigData #Statistics #Python #Programming #Coding #EDA #AI #ArtificialIntelligence #MachineLearning #DeepLearning #ReinforcementLearning #TensorFlow #Keras #NeuralNetwork #Innovation #Startups #Tech #Automotive #Semiconductor #MatrixThinking #GaN #DataCenter #Technology #Job #Careers #Hiring #LinkedIN #Jobs #OpenToWork #Learning #JobOpening #Mathematics #Production #Productivity #Opportunities #Strategy #FAB #Foundry #Software #Correlation #Methodology

We will probably see a decline in the number of openings for two roles in the field of Data Science in the next few years. One of them being the role of Data Scientist. Yes, that’s the title that I’ve worked with for many years and now I have a hunch that the openings will go down. The second one is the MLOps Engineer. As Data Science techniques matured in the industry, we had seen an increase in the need for ML and MLOps Engineers. Solutions had started moving from the prototype/MVP stage to production. But then came GenAI. And now it’s back to experimentation again with the new normal in the world of Data Science. You may ask, where do the Data Scientists go? Here’s some good news for Data Scientists. You go nowhere! But on one condition. You upskill yourself with building GenAI solutions. Then you open up the AI Engineer role for yourself. So, in essence, there’s going to be a decline in openings for Data Scientists and an increase in openings for AI Engineers. Or to put it in another way, Data Scientists + GenAI = AI Engineers On MLOps Engineers, the number of openings will probably go down, until they start going up again in another 3-4 years. Oh, and ML Engineers openings might also go up as companies start to use AI and ML interchangeably. This is how I see the space for different job roles in the Data Science industry evolve in the next few years. What do you think? #datascience #machinelearning #genai

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This is such a well compiled document Shivam Modi 👌🔥