Andre Chapman’s Post

Happy Wednesday! Today’s AI job market is buzzing, and we’ve rounded up the top opportunities just for you, check them out! 👇 🔥 1. Copeland - Data Engineer (Azure Cloud) What's the role? Build and maintain data warehouses at Copeland. Collaborate with teams, optimize data workflows, and implement new datasets for customer-facing products. Why Copeland? Copeland is scaling fast with a 25% headcount increase to 3,135! Engineering expanded by 20% and HR support grew 15%. They’re investing in talent—great for AI job seekers! 🔥 2. Consolidated Communications - Analytics Data Engineer What's the role? Transform and load data from various sources using Oracle, AWS, and SQL at Consolidated Communications. Support analysis, ensure data quality, and collaborate with teams to enable insights on business performance. Why Consolidated Communications? Consolidated Communications is making waves! 25% headcount growth signals ambition with a total of 1759 employees. Engineering expanded 30%, but biz dev is where the real action is. Ideal for AI talent! 🔥 3. Demandbase - Senior Data Engineer What's the role? Build Demandbase's next-gen unified data platform. Create data pipelines, work with massive data sets, and ensure quality and accessibility. Use Airflow for orchestration. Why Demandbase? Demandbase is on the rise with 20% headcount growth, now at 963. Engineering team expanded 25%, indicating a strong tech focus. HR up 15%, showing they value their people. Ideal for AI talent seeking growth! 🔥 4. Hytrol - Data Engineer Intern - Jonesboro, AR What's the role? Manage data flows and monitor pipelines at Hytrol. Write SQL queries, design database tables, and tackle real projects. Gain hands-on data engineering experience. Why Hytrol? Hytrol's booming with a 35% headcount increase! Engineering team up 40% in a year, proving they're serious about tech growth. HR support at 15% shows they value their people. Great spot for AI talent ready to dive into a thriving environment! 🔥 5. MMIT (Managed Markets Insight & Technology) - Data Engineer What's the role? Analyze, design, develop, and maintain tech solutions using SSIS and T-SQL at MMIT. Create reports, manage data, and collaborate with teams. Keep learning and coding! Why MMIT (Managed Markets Insight & Technology)? MMIT is on the rise with 25% growth in headcount, now at 472. Engineering expanded 30% – tech talent wanted! HR is at 15%, showing they care. Solid investment in their workforce, ideal for AI pros! And as always, check the first comment for links to apply🫡 Last thing, no sponsorships here - Just our team scouting the best opportunities across the AI space. #AI #BigData #cloudcomputing

Writing a Good Job Description for Data Science/Machine Learning Things to do and things to avoid in order to find the right candidates for your open position Photo of a very good candidate by Thomas Butler on Unsplash I’ve probably been involved in the hiring process for data scientists a dozen times or more over my career, while never being the hiring manager myself, and I have been closely involved in writing the job description for several of these. It kind of seems like this should be easy — you’re just trying to convince people to apply for your job, so you can pick the one you like best, right? Well, it’s actually more complicated than that. Most of the people out there in the world are not qualified for any given job, and even among those who are qualified, there may be reasons they wouldn’t like working in this role. It’s not a one-way street; you don’t want just anybody to apply, you want the best suited people, for whom this job would work, to apply. So, how do you thread that needle? What should you write? This column is only my opinion and does not represent the views of my employer. I have not been involved in writing any job descriptions my current employer has posted, for ML or anything else. Why write a Job Description? To figure out what to write, let’s break down what it is a good job description is supposed to do, for a DS/ML job or for any other kind. Explain to candidates what the job is, and what they would do in the job Explain to candidates what qualifications you’re looking for in applicants These are the bare essential functions, although there are several other things your job description posting should also do: Make your organization seem like an attractive place to work for a diverse pool of qualified candidates Describe the compensation, work circumstances, and benefits, so candidates can decide whether to bother applying With this, we’re starting to get into more subjective and complicated components, in some ways. In some spots, I’m going to give advice for two different scenarios: first, for a small organization with few or zero existing DS/ML staff members, and second, for a medium or large sized organization with some DS/ML staff. These two can be quite different situations, with different needs and challenges in certain areas. You may notice I’m using “DS/ML” a lot in this article — I consider the advice here good for people hiring data scientists as well as those hiring machine learning engineers, so I want to be inclusive where possible. Sorry it’s a little clunky. What is this job? Firstly, for any organization, consider what kind of role you have open. I’ve written in the past about the different kinds of data scientist, and I’d strongly recommend taking a look and seeing what archetypes your role fits into. Think about how this person will fit into your organization, and be clear about that as you proceed. The Small Organization A challenge, especially for small organizations with ...

You need practical experience to get a job as a data scientist. True! You need a job to get practical experience in data science. True! Seems like a deadlock, right? But sadly, this is true. Today, companies are unwilling to try to train people in data science and start their requirements by mentioning prior experience in data science, even for beginner roles. But how can you gain the experience without working? If you just show courses and certifications in your resume, the hiring manager will reject it within 30 seconds. Even if you are great in algorithms and ML theory, you will not get the chance for an interview. Another problem. Many companies hire data scientists, but they mostly do reporting and bug fixing, so they never get any practical experience. After working for some time, they feel frustrated because the job is not up to their expectations. They also cannot switch jobs easily because they don’t have any notable experience. Many tried to fake it but got rejected in the screening round itself. So, the biggest question for every aspirational data scientist is: How can they break this cycle? How can they gain at least some practical experience, which they can put in their resumes and at least get a fair chance for an interview? The answer: Exposure to Enterprise-Grade Data Science Projects! You start with a problem statement, get the data needed, do feature engineering, apply models, and measure performance. Cool right? But you cannot do just any project. Your projects should be: - Unique (And not like iris classification or titanic survival) - Brings value - Impactful - Based on current market trends (Super Important) I have been researching this and found the perfect website - ProjectPro. They have some unique enterprise-grade projects that can be used for learning and portfolio building. Some of my favorites are: - Fine-tune Large Language Model for Advanced Chatbot - Langchain Project for Customer Support App in Python - Llama2 Project for MetaData Generation using FAISS and RAGs - MLOps Project to Build Search Relevancy Algorithm with SBERT - Build a recommendation engine like Amazon They have a list of 250+ projects and cover almost all the areas of data engineering and data science. Check them here - https://bit.ly/3w4vQVv They are not only projects but are explained perfectly, so you can describe them in interviews with all the technical details and reasons for selecting any specific model and evaluation metrics. That makes your profile strong for any relevant data science role. Share it with others! #datascience #machinelearning #nlp #llm #projecrts #ds #ai #ml #jobs

Today’s standout AI job opportunities are in, and our team has cherry-picked the gems just for you. Check them out. 🔥 1. Orion Innovation - Big Data Engineer What's the role? Analyze requirements, design and optimize big data pipelines, develop and support Hadoop jobs, and enhance existing applications at Orion. Monitor real-time data flow and interact with clients for architecture input. Travel across the US as needed. Why Orion Innovation? Orion Innovation is booming with 40% headcount growth, now 4,376 strong! Engineering team expanded 25%, signaling hunger for tech talent. HR up 30%, showing they prioritize employee well-being. Perfect for AI job seekers! 🔥 2. Altamira Technologies Corporation - Data Engineer What's the role? Manage data pipelines, optimize performance, and ensure secure data transfer at Altamira in Tampa, FL. Collaborate on TQD tool operations and report generation. Why Altamira Technologies Corporation? Altamira Technologies Corporation is booming with a headcount growth of 40% in a year, now at 350. Engineering team expanded 30%, showcasing a push for talent. Perfect for AI job seekers aiming to join a fast-growing tech environment! 🔥 3. DRC Systems - Data Engineer - AWS What's the role? Design and maintain data solutions, gather requirements, and work with teams to deliver analytics. Lead best practices and coach junior engineers. Manage cloud services and ensure data quality. Why DRC Systems? DRC Systems, with 324 employees, shows solid growth. Engineering up 30%, signaling a tech focus. Biz dev surged 40%, indicating ambition. HR team expanded, highlighting employee care. Ideal for AI talent! 🔥 4. Halvik - Senior Data Engineer AI/ML What's the role? Manage employee benefits like insurance and PTO at Halvik Corp. Handle 401(k) matching and tuition assistance. Ensure compliance and support hiring processes. Why Halvik? Halvik is on the rise! With 191 employees, they’ve seen a 40% growth. Engineering team expanding and HR is strong, showing they value their talent. Great spot for AI job seekers. 🔥 5. Homebot - Senior Data Engineer What's the role? Build and maintain data pipelines, ship new data products, and ensure high-quality data delivery at Homebot. Collaborate with teams to solve data issues. Why Homebot? Homebot is on the rise! With 40% headcount growth, now at 105 employees, their engineering team grew 50%—they're hungry for tech talent. Strong HR focus shows they care about their people. Great for AI job seekers! And as always, check the first comment for links to apply🫡 Last thing, no sponsorships here - just our team scouting the best opportunities across the AI space.

Data science continues to be a highly sought-after skillset in 2024, with its applications spanning across various industries. Here's how data science can boost your career this year: High Demand: Organizations across industries continue to recognize the value of data-driven decision-making. As a result, there's a high demand for data scientists who can collect, analyze, and interpret data to drive business strategies, product development, marketing campaigns, and more. Versatility: Data science skills are versatile and applicable across a wide range of industries, including healthcare, finance, retail, e-commerce, entertainment, and more. This versatility allows data scientists to explore various career paths and find opportunities in sectors that align with their interests and expertise. Salary Potential: Data scientists command competitive salaries due to the high demand for their skills. In 2024, data science professionals can expect lucrative compensation packages, including base salary, bonuses, and other perks. Career Progression: Data science offers ample opportunities for career growth and advancement. Professionals can progress from entry-level roles to senior positions such as data scientist, data analyst, machine learning engineer, AI specialist, data architect, and more, depending on their experience, skills, and expertise. Continuous Learning: The field of data science is dynamic, with new technologies, tools, and techniques constantly emerging. As such, there's always something new to learn, allowing professionals to stay engaged and continuously upskill themselves to remain competitive in the job market. Remote Work Opportunities: The rise of remote work has expanded job opportunities for data scientists, allowing them to work for companies located anywhere in the world. This flexibility enables professionals to pursue remote positions that offer work-life balance and cater to their personal preferences. Impactful Work: Data science enables professionals to work on meaningful projects that have a significant impact on businesses, society, and the world at large. Whether it's analyzing healthcare data to improve patient outcomes, optimizing supply chains to reduce waste, or developing predictive models for climate change, data scientists have the opportunity to make a difference through their work. Overall, data science offers a promising career path in 2024 and beyond, providing professionals with opportunities for growth, competitive compensation, and the ability to contribute meaningfully to various industries and societal challenges. Enorll for JAM/GATE/ISI/CUET-Statistics Subscribe the channel for more: https://lnkd.in/gUa7f_Fs Follow LinkedIn-: https://lnkd.in/gVn7auQT ✅ Visit Supremum Website for more information: supremum.in If you have any query related with anything Please 📞 Call Us at *_+91 78276 04354_* Regards Supremum Classes #IITJAM #ISI #CUET #GATE #DATA_SCIENCE

Top 5 Data Science Jobs in 2024 In the Fast Paced world of Technology, Data Science has emerged as a Leading field people want to Pursue, offering Tremendous career prospects. With the increasing reliance on data driven decision making, the demand for skilled Data Scientists is at an all time high. If you’re considering a career in Data Science, it’s essential to explore the Top Job roles that will be in demand in 2024. This blog post highlights the Top 5 Data Science Jobs in 2024 that promise exciting opportunities and growth potential. https://lnkd.in/ek9RkJnP #Hiring #Jobs #AI #ML #AIJobs #MLJobs #AImployed #Machinelearning #AImployedLaunch #AIRevolution #FutureOfWork #AIJobs #CareerDevelopment #TechCommunity #JoinUs #UnlockYourPotential #AIEngineering #TechInnovation #DataDriven #AIInnovation #DigitalTransformation #TechLeadership #TeamCollaboration #AIPrototyping #GrowthConsultancy #TechCareer 

Today’s roundup of the must-have Data & AI job openings is here—curated for your convenience. Discover your next opportunity below… 🔥 1. Qlik - Sr Machine Learning Engineer What's the role? Develop cutting-edge AI products at Qlik. Collaborate with teams to build user-friendly AI solutions, tackle various projects, and enhance organizational insights. Why Qlik? Qlik is booming with 3937 employees, showing 20% growth. Engineering surged 30% recently—huge demand for technical talent! HR jumped 15%—they value their people. A great moment for AI pros to join a thriving team! 🔥 2. UMB Bank - Sr. Data Engineer What's the role? Build and maintain data pipelines at UMB. Modernize systems, implement cloud strategies, and manage data processing. Analyze and visualize data for insights. Why UMB Bank? UMB Bank is booming with 12% headcount growth! Engineering hiring up 15% indicates a tech focus. HR grew 20%, showing they prioritize their people. Ideal for data pros seeking stability and growth! 🔥 3. Motiva Enterprises LLC - Data Engineer What's the role? Design and build data pipelines at Motiva, focusing on analytics and reporting. Collaborate with teams, integrate data sources, and optimize dashboards. Drive insights and enhance data governance. Why Motiva Enterprises LLC? Motiva Enterprises is on a growth spree with a headcount of 2,660. Engineering up 15%, signaling tech investment. HR growth shows strong focus on employee satisfaction. If you're in AI, they’re ripe for talent! 🔥 4. Spring Health - Senior Machine Learning Engineer I What's the role? Build and enhance AI models for precision mental health at Spring Health. Develop new data products, improve recommendations, and optimize care journeys. Why Spring Health? Spring Health is booming with a workforce of 2,490, showing a 40% growth in engineering. HR is prioritized, indicating strong team support. Join for a thriving tech-focused culture! 🔥 5. Blue Cross Blue Shield of North Dakota - Healthcare Data Scientist What's the role? Analyze complex healthcare datasets to find trends that inform decisions. Collaborate with teams, build predictive models, and communicate insights. Use Python or R for modeling. Why Blue Cross Blue Shield of North Dakota? Blue Cross Blue Shield of North Dakota: 847 employees, growing HR by 20% shows they value their people. Engineering stays steady, indicates a solid tech base. Great for AI talent seeking stability! And as always, check the first comment for links to apply🫡 Last thing, no sponsorships here - Just our team scouting the best opportunities across the AI space.

How to Become a Data Scientist in 2024 Data Science, a field that involves extracting valuable insights from the vast pool of data, is rapidly evolving and offers exciting Career Opportunities. Organizations worldwide rely on Data Scientists to help them make informed decisions, optimize operations, and drive innovation. In this comprehensive guide, we will walk you through a step by step roadmap on How to Become a Data Scientist in 2024. We’ll cover everything from the Qualifications and Skills required to the Career prospects and the Latest trends in the Field of Data Science. In today’s digitally driven world, organizations accumulate an unprecedented volume of data. This data is a goldmine of information waiting to be unlocked, and Data Scientists are the key to this treasure trove. They are the professionals who specialize in analysing and interpreting data, providing insights that guide strategic decisions and lead to innovations. https://lnkd.in/eVJ569bg #Hiring #Jobs #AI #ML #AIJobs #MLJobs #AImployed #Machinelearning #AImployedLaunch #AIRevolution #FutureOfWork #AIJobs #CareerDevelopment #TechCommunity #JoinUs #UnlockYourPotential #AIEngineering #TechInnovation #DataDriven #AIInnovation #DigitalTransformation #TechLeadership #TeamCollaboration #AIPrototyping #GrowthConsultancy #TechCareer 

Looking for a job in data, analytics, or AI? Then Andre Chapman is a great follow. I've known Andre for years and there's not a better human in the recruiting biz. #data #analytics #AI #DataJobs #datastrategyisbusinessstrategy

What specific aspects or questions do you have in mind about time series forecasting projects?