Meet our newest team member, Angelie! She was formerly an intern for the Data Team and now works full-time as a Data Scientist and Engineer at CareerVillage. She graduated from the University of Chicago with a Bachelor’s in Data Science and plans to stay in Chicago. When she is not working, she likes to crochet and read. WELCOME, ANGELIE! 🧡🧡
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"Excited to share that I'll be interning with Excelr in their Machine Learning and Data Science division! This opportunity will allow me to dive deep into data analytics, gain hands-on experience with machine learning algorithms, and contribute to real-world projects. Looking forward to growing my skills and knowledge in this dynamic field!"
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Let's give them some spotlight!! 🎉 We're super excited to welcome four new faces to our team, all stars from the VU Amsterdam and ready to make their mark. Yas Farahani is diving into business development with us, driven purely by her passion for the field. She's here to shake things up, and we're all for it. Then we've got a power trio of Data Scientist interns - Maurits de Vries, Syb Heringa, and Romnick Mozes Evangelista. They're here to crunch numbers, weave data magic for their thesis, and, honestly, teach us a thing or two about customer success along the way. It's not just about what they learn here, but also what we learn from them. Fresh perspectives, new ideas, and a whole lot of energy - that's what we're all about. So, a big welcome to Yas, Maurits, Syb, and Romnick. Can't wait to see the awesome things we'll achieve together. Let the adventure begin! 🚀 #NewBeginnings #TeamChurned #DataScience #BusinessDevelopment
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Aspiring Data Analyst | Open for Internships | Skilled in Python, Machine Learning, Data Visualization, and SQL
🚀 Excited to share that I've successfully completed Task 1 of my Data Science Internship at Encryptix, working on the Titanic Survival Prediction project! 🛳️ 📊 Project Overview: I delved into the Titanic dataset to predict passenger survival, leveraging key features like age, gender, and class. Through this project, I focused on: • Data Preprocessing: Cleaning and preparing the data for analysis. • Feature Engineering: Crafting new features to enhance model performance. • Model Optimization: Fine-tuning algorithms to boost prediction accuracy. This hands-on experience sharpened my skills in data visualization, statistical analysis, and machine learning, fueling my passion for data-driven problem-solving. I’m eager to apply these insights to future projects and continue growing in the field of data science! 🔗 Check out the project on GitHub: https://lnkd.in/d_4DJbtu
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Calling all folks in central Ohio who work at companies of *any* size that have data! This month's Columbus Data & Analytics Wednesday will be on Wednesday, 9/18, in the Arena District (at Denison Edge) and will feature a panel from local universities discussing the what, why, and how of bringing on an analytics or data science intern. Register: https://lnkd.in/gfjnKYeS I'm convinced this is an absolute win-win situation: bright students need real world experience when they graduate; companies can always use more bright and talented minds to point at analytics challenges (and...shhh!!!... interns are low cost!). I'm hoping for a strong turnout (bring the colleague you'll most need to convince! Remember: we have prizes when you bring a first-timer friend). Sure, this topic/format was my idea, and I'd love some personal validation. But, *more* importantly, I'd love to get some wheels turning in the minds of local companies that lead to some great work next summer! So, Andy Shockney, Anna Sinitsyna, Tony Zara, Dave Cherry, Neil Collins, Jenna Murry, Lauren Burke-McCarthy, Olga Verbytska, Pauline Gaynesbloom, Julie Wilson, PMP, let's get the word spread!
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"🎉🎉I'm excited to share that I've completed Level 3 (Task 3), during my tenure as a Data Scientist intern at Cognify Technologies. Grateful for the learning opportunities and looking forward to applying my skills to new challenges! 🌟📚 Task 3: Data Visualization Create visualizations to represent the distribution of ratings using different charts (histogram, bar plot, etc.). Compare the average ratings of different cuisines or cities using appropriate visualizations. Visualize the relationship between various features and the target variable to gain insights.
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Congratulations to our Intern of the Week, Amandeep Sohal. Amandeep is a computer science major with a concentration in information systems. His favorite thing about working at MERC is “Working with data and getting hands-on experience”. After graduation, he plans on either getting a job in data analytics or pursue a masters in data analytics. His favorite hobby is baking. His favorite TV show is 𝑀𝑎𝑠𝑡𝑒𝑟 𝐶ℎ𝑒𝑓: 𝐶𝑎𝑛𝑎𝑑𝑎 and his favorite movie is 𝐿𝑖𝑙𝑜 & 𝑆𝑡𝑖𝑡𝑐ℎ.
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I’m excited to share that I have successfully completed Task 5 of my data science internship at #ProdigyInfotech where I focused on analyzing traffic accident data to uncover insightful patterns related to road conditions, weather, and time of day. Key Highlights: Pattern Identification: I examined how various factors such as road conditions (e.g., wet or dry), weather conditions (e.g., rainy or foggy), and different times of day impact the frequency and severity of traffic accidents. Visualization: Using advanced data visualization techniques, I created heatmaps and charts to pinpoint accident hotspots and identify contributing factors. This visual representation not only highlights critical areas but also aids in understanding the underlying trends. Insightful Findings: The analysis revealed significant patterns, such as higher accident rates during certain weather conditions and specific times of day. These insights are crucial for developing strategies to enhance road safety and improve traffic management. This task has not only deepened my understanding of data analytics but also demonstrated the real-world impact of data-driven decision-making in improving public safety. I’m grateful for the opportunity to apply my skills in such a meaningful way! A big thank you to my mentors and team members for their support and guidance throughout this project. I look forward to tackling more challenges and continuing to grow in my data science journey. #ProdigyInfotech #DataScience #DataVisualization #InternshipExperience #ProfessionalGrowth The link to the task - https://lnkd.in/gt8vYQdh
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Associate Data Scientist | Information Communication Technology, Economics, & Political Science Student
Yesterday, I completed a full #year at World Data Lab ✨ Reflecting on these past 12 months makes me even more excited about what’s to come. Working as an intern during a summer of full-time engagement and continuing part-time, I've had the privilege to: • Collaborate with 8 diverse #clients (public and private sectors) • Create and deliver over 20 #presentations, 4 detailed #reports, 4 #blog posts, and 2 sets of release notes about our granular #data • Contribute to significant #publications from our partners • Assist in 5 #webinars and 3 strategic client #meetings • Get 6 #insights published I joined the company when the 1st World Consumer Outlook was being created. Currently, I am helping build WCO 3 (!!), which will be held on May 29th — detailed data, insightful updates, and special guests 🌎 Sign up here: https://lnkd.in/dP3UpgsV (In the photo, a few of the amazing people I get/have gotten to work with!)
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🎉 Excited to share that I've successfully completed my first task as a Data Science Intern at #congifyz #congifyztech 🚀 During this initial project, I: 🔍 Analyzed the distribution of the target variable "Aggregate Rating" 🔄 Performed data type conversion from float to integer 📊 Visualized the data to identify any class imbalances
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Software development enthusiast | Electric vehicle enthusiast | Data Science Enthusiast | Electronics and telecommunications Engineer
🚀 Thrilled to have completed Task 1 of Data science internship at Encryptix on Titanic Survival Prediction! 🛳️ Task 1 Github Link: https://lnkd.in/e3avefGC In this project, I explored and analyzed the famous Titanic dataset to predict passenger survival based on various features such as age, gender, and class. I developed a predictive model, focusing on data preprocessing, feature engineering, and model optimization to improve accuracy. This hands-on experience deepened my understanding of key data science concepts, including data visualization, statistical analysis, and machine learning. I’m excited to continue leveraging these skills in future data-driven projects!
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Resident Director at KCJS: Kyoto Consortium for Japanese Studies
2moCongratulations, Angelie!