#internships data analyst

[stuintern01]

Looking to start a career in data science? This guide offers essential tips and expert advice to help you build a strong foundation, master key tools, and navigate the job market. Learn how to create a compelling portfolio, connect with industry professionals, and stay competitive in this fast-growing field. Kickstart your data science journey today and unlock your potential for a rewarding career

[averruncusho]

SO i’m going to do a research project, while doing a part-time internship, while being president of 3 major clubs, while overloading my academic schedule. Really hope I can hold things together this semester 😬

[evisiontechnoserve]

Fastest Growing IT Roles in India 2025 Edition

Step into the most in-demand tech careers of 2025 with Evision Technoserve! Explore top career paths such as Cloud Administrator, Cybersecurity Analyst, AI & Data Science Engineer, Full Stack Developer, and DevOps Engineer. Gain real-world experience through hands-on projects and learn directly from industry mentors. Evision’s expert-led training programs are designed to fast-track your IT career with 100% placement assistance. Don’t miss out on exciting internship and job opportunities

[flexispheres]

Consultant – Labour Migration

Consultant – Labour Migration Location: Ankara, Turkey Application Deadline: 3 July 2025, 11:59 PM Contract Type: Consultancy (up to 11 months) Job Category: Labour Migration, Employment Policy, Capacity Development Education Required: Bachelor’s degree minimum (Master’s or PhD preferred) Languages Required: English and Turkish Organizational Unit: International Organization for Migration (IOM) –…

[datagenie]

Marketing Insight Report

Introduction: This report analyzes retail sales transaction data obtained from Kaggle. The tabular dataset consists of both categorical and numerical data types with 13 columns detailing sales transactions in various stores across the United States. The objective is to identify key insights including top-selling products, customer segment trends, and other actionable findings that will allow further analysis. The data was explored using Microsoft Excel.

Observations

High Revenue Generating Products

After the first review of the dataset, it can be observed that Phones generated the highest revenue, followed closely by Chairs and Storage. Other products like Binders and Tables also had a strong performance. This indicates that Technology and Furniture categories drive major revenue for the business.

2. Demand Drivers: Binders and Paper had the highest unit sales volume, indicating strong demand and frequent repeat purchases. However, Binder sales appear to be largely driven by discounts, impacting profitability. This suggests exploring bundling strategies with complementary products such as Paper or Storage to reduce reliance on discounts.

3. Customer Segment Trends: The Consumer segment generated the highest sales, followed by Corporate and Home Office customers and this emphasizes that the direct-to-consumer is the primary revenue driver. The Consumer segment also accounted for the highest profits which further highlights their significance to the business.

Conclusion The initial analysis of the dataset uncovered insights into the sales and profitability of the retail stores. It highlights the top revenue-generating products as Phones and Chairs while individual consumers form the largest customer segment. Future marketing efforts should focus on this category of consumers and further analysis could investigate the impact of discounts on profitability and understanding customer purchase frequency and average order value to identify opportunities for increasing sales.

For more information about the HNG Internship program, please visit HNG Internship and HNG Hire.

[stuintern1]

Turn Data into Insights with StuIntern!Master the art of Data Analytics with StuIntern's Certificate Programme.

✅ Hands-on projects in predictive modelling ✅ Internship certification for your career ✅ Budget-friendly and flexible learning

Enroll today and shape your future with StuIntern!

[khayalonsebunealfaz]

Data Science 2.0: The Future of Intelligent Insights 

Data science is developing quickly in the current digital era, changing how various sectors function. Data science 2.0 is a revolutionary stage in which machine learning (ML), artificial intelligence (AI), and data analytics come together to produce insights that can be used immediately. This change pushes the limits of data science to become more automated and predictive, going beyond conventional data analysis. Businesses that use Data Science 2.0 are able to predict trends, streamline processes, and provide individualized customer service. We'll examine the essential elements of this development in this post and discuss why Data Science 2.0 is so important for companies looking to maintain their competitiveness. 

The Rise of Automation in Data Science: 

A key component of Data Science 2.0 is automation, which streamlines the data process. Once laborious, tasks like data transformation, processing, and cleansing are now managed by sophisticated algorithms. Instead of manually preparing data, automation enables data scientists to concentrate on higher-level problem-solving. AI-powered technologies, for example, may spot trends in data, which lowers the possibility of human error. This automation improves the accuracy of insights while also speeding them up. Automation in data science provides businesses with quicker, more accurate insights that enhance decision-making. 

Enhancing Precision with Machine Learning: 

Data scientists can now create accurate, dynamic models thanks to machine learning, which deepens Data Science 2.0. By learning from past data, these models are able to forecast patterns and provide focused insights. ML algorithms, for instance, can be used by retail companies to predict changes in demand based on consumer behavior. Accurate forecasting and tailored suggestions are made possible by machine learning, which increases precision and adds value for businesses. As machine learning technology develops, it will play an increasingly important role in data science by transforming massive numbers into understandable, useful insights. 

Real-Time Analytics for Rapid Decisions: 

Real-time analytics is among the most intriguing features of Data Science 2.0. Real-time analytics, as opposed to traditional data processing, offers immediate insights, enabling firms to take immediate action. This skill is especially useful in sectors where timing is crucial, such as e-commerce, healthcare, and banking. Better conversions and consumer happiness can result from an online retailer's ability to adapt prices in real-time based on user activity. Businesses may be proactive rather than reactive with real-time data processing, which puts them in a successful position in cutthroat industries. 

Conclusion: 

A new era marked by automation, machine learning, and real-time analytics is heralded by the development of data science into Data Science 2.0. These developments transform how businesses function by enabling data-driven decision-making to be done quickly, accurately, and adaptably. Businesses may use data to promote efficiency and growth by adopting Data Science 2.0, giving them a strategic edge. A Data Science internship provides hands-on experience for people wishing to enter this rapidly changing sector, assisting aspiring data scientists in comprehending the requirements of contemporary analytics. In a data-driven world, embrace Data Science 2.0 to unleash your potential for innovation, adaptation, and leadership. 

[heyexcelr]

How to Choose the Right Data Analyst Specialization for Getting Better Results as an Intern

In the dynamic field of data analytics, specialization is becoming increasingly important. As data-driven decision-making continues to grow across industries, organizations seek data analysts with specialized skills that align with their specific needs. For students and aspiring data analysts, choosing the right specialization can significantly impact your internship experience and, ultimately, your career trajectory. This article explores how to choose the right data analyst course specialization to achieve better results as an intern.

1. Understand the Core Specializations in Data Analytics

Before diving into the process of choosing a specialization, it’s essential to understand the core areas within data analytics. While the field is vast, there are several common specializations that data analysts can pursue:

Data Engineering: Focuses on building and maintaining the infrastructure that allows data to be collected, stored, and analyzed efficiently. Data engineers work with databases, data warehouses, and big data technologies.

Data Visualization: Involves creating visual representations of data to help stakeholders understand complex information quickly. Specialists in this area use tools like Tableau, Power BI, and D3.js to develop interactive dashboards and reports.

Machine Learning: Combines statistical analysis and algorithm development to create predictive models. Machine learning specialists often work with Python, R, and specialized libraries like TensorFlow and Scikit-learn.

Business Analytics: Concentrates on applying data analysis to solve business problems. Business analysts interpret data to inform strategic decisions, often working closely with stakeholders to understand their needs.

Statistical Analysis: Involves applying statistical techniques to interpret data, test hypotheses, and predict outcomes. This specialization is crucial for fields like finance, healthcare, and market research.

2. Assess Your Interests and Strengths

Choosing the right specialization starts with a self-assessment. Reflect on the aspects of data analytics that you find most engaging and where your strengths lie. For example:

Do you enjoy working with large datasets and optimizing data pipelines? If so, data engineering might be the right fit for you.

Are you passionate about creating visuals that tell a story? Data visualization could be your ideal specialization.

Do you have a strong background in statistics and enjoy building models? Machine learning or statistical analysis might be where you excel.

This self-assessment will help you identify which specialization aligns with your natural abilities and interests, making your internship more enjoyable and productive.

3. Research Industry Demand and Trends

While your interests are crucial, it’s also important to consider the current demand for different specializations in the job market. Research the industries that are hiring data analysts and the specific skills they are looking for.

Look at Job Postings: Browse job boards and company websites to see what specializations are in high demand. For instance, industries like finance and healthcare may have a higher demand for specialists in statistical analysis, while tech companies may prioritize machine learning experts.

Consider Future Trends: Pay attention to emerging trends in data analytics. For example, as more companies adopt artificial intelligence, the demand for machine learning specialists is likely to grow. Similarly, the increasing importance of data-driven decision-making in all sectors means that business analytics will continue to be a sought-after specialization.

4. Seek Guidance from Mentors and Industry Professionals

Mentorship can be invaluable when choosing a specialization. Seek advice from professors, industry professionals, or even peers who have already completed internships. They can provide insights into the day-to-day responsibilities of different specializations and help you understand which areas are most relevant to your career goals.

Join Professional Networks: Engage with professional organizations and attend industry events or webinars. Networking with professionals in your field can give you a better understanding of what different specializations entail and what employers are looking for.

Request Informational Interviews: If possible, set up informational interviews with data analysts working in your area of interest. Ask them about the skills required, the challenges they face, and the opportunities for growth in their specialization.

5. Consider the Internship Opportunities Available

Finally, the availability of internship opportunities can influence your choice of specialization. Some specializations may have more internship openings than others, depending on the industry and location.

Research Companies: Look into companies that offer internships in your desired specialization. For example, tech companies might offer more opportunities in machine learning, while consulting firms might focus more on business analytics.

Evaluate Internship Descriptions: Read internship descriptions carefully to ensure they align with your chosen specialization. Look for internships that offer hands-on experience in the specific skills you want to develop.

Conclusion

Choosing the right data analyst specialization is a crucial step in maximizing your internship experience and setting the stage for a successful career. By understanding the core specializations, assessing your interests and strengths, researching industry demand, seeking guidance from mentors, and considering available internship opportunities, you can make an informed decision that aligns with your career goals.

The right specialization will not only enhance your skills and knowledge but also position you for better results during your internship and beyond. As you embark on your journey as a data analyst after choosing a data analyst course in vizag wisely, remember that specialization is not just about narrowing your focus—it’s about deepening your expertise in an area that excites you and aligns with industry needs, ultimately leading to a more fulfilling and successful career.

ExcelR — Data Science, Data Analyst Course in Vizag

Address: iKushal, 4th floor, Ganta Arcade, 3rd Ln, Tpc Area Office, Opp. Gayatri Xerox, Lakshmi Srinivasam, Dwaraka Nagar, Visakhapatnam, Andhra Pradesh 530016

Mobile number: 7411954369

[neuailabs]

Uncover the World of Data Science in Pune

Discover the endless possibilities of data science through our immersive course in Pune. Gain expertise in analyzing data, extracting insights, and driving informed decisions. Equip yourself with essential skills for today's data-driven world with NeuAI Labs.

[uniquejobs]

Truck Manufacturing Company Hiring | UD TRUCKS | Senior Data Analyst - Quality Assurance role - apply now

Introduction Truck Manufacturing Company Hiring: UD Truck has Published notification for the vacancy of  Data Analyst The educational qualification required to apply for this UD Truck is B.E ,B.Tech Engineers Interested and eligible candidates can apply for UD Truck. There is enough time to apply for any job. Read UD Truck date, last date to apply, full details of vacancies carefully. As per…

[askagamedev]

Summer 2025 Game Development Student Internship Roundup, Part 2

Internship recruiting season has begun for some large game publishers and developers. This means that a number of internship opportunities for summer 2025 have been posted and will be collecting applicants. Internships are a great way to earn some experience in a professional environment and to get mentorship from those of us in the trenches. If you’re a student and you have an interest in game development as a career, you should absolutely look into these.

This is part 2 of this year's internship roundup. [Click here for part 1].

Associate Development Manager Co-op/Internship - Summer 2025 (Sports FC QV)

Game Product Manager Intern (Summer 2025)

Music Intern

EA Sports FC Franchise Activation Intern

Associate Character Artist Intern

Client Engineer Intern

Visual Effects Co-Op

Associate Environment Artist Co-Op (Summer 2025)

Game Design Intern (Summer 2025)

Game Design Co-Op (Summer 2025)

Concept Art Intern - Summer 2025

UI Artist Intern - Summer 2025 (Apex Legends)

Assistant Development Manager Intern

Global Audit Intern

Creator Partnerships Intern - Summer 2025

Technical Environment Art Intern - Summer 2025 (Apex Legends)

Intern, FC Franchise Activation, UKI

Tech Art Intern - Summer 2025 (Apex Legends)

Software Engineer Intern

UI Artist Intern

Game Designer Intern

FC Franchise Activation Intern

Software Engineer Intern

Product UX/UI Designer

Software Engineer Intern

Enterprise, Experiences FP&A Intern

Game Designer Intern

Software Engineer Intern

Development Manager Co-Op (Summer 2025)

Software Engineer Intern

PhD Software Engineer Intern

Character Artist Intern

2D Artist Intern - Summer 2025

Software Engineer Intern (UI)

Entertainment FP&A Intern

Game Design Co-Op (Summer 2025)

Data Science Intern

Production Manager Intern

Software Engineer Intern

Channel Delivery Intern

FC Pro League Operations Intern

World Artist Intern

Experience Design Co-Op

Media and Lifecycle Planning Intern

Software Engineer Intern - Summer 2025

Software Engineer Intern - Summer 2025

Intern, FC Franchise Activation, North America

Creative Copywriter Intern

Game Design Intern

Social Community Manager Co-Op

Business Intelligence Intern

Software Engineer Intern (F1)

Total Rewards Intern - MBA level

Intern - Office Administration

Digital Communication Assistant – Internship (6 months) february/march 2025 (W/M/NB)

International Events Assistant - Stage (6 mois) Janvier 2025 (H/F/NB)

Intern Cinematic Animator

Research Internship (F/M/NB) - Neural Textures for Complex Materials - La Forge

Research Internship (F/M/NB) - Efficient Neural Representation of Large-Scale Environments - La Forge

Research Internship (F/M/NB) – High-Dimensional Inputs for RL agents in Dynamic Video Games Environments - La Forge

Research Internship (F/M/NB) – Crafting NPCs & Bots behaviors with LLM/VLM - La Forge

3D Art Intern

Gameplay Programmer Intern

Intern Game Tester

Etudes Stratégiques Marketing – Stage (6 mois) Janvier 2025 (F/H/NB)

Localization Assistant– Stage (6 mois) Avril 2025 (F/H/NB)

Fraud & Analyst Assistant - Stage (6 mois) Janvier 2025 (F/H/NB)

Payment & Analyst Assistant - Stage (6 mois) Janvier 2025 (F/H/NB)

Media Assistant – Stage (6 mois) Janvier 2025 (F/H/NB)

IT Buyer Assistant - Alternance (12 mois) Mars 2025 (H/F/NB)

Event Coordinator Assistant - Stage (6 mois) Janvier 2025 (H/F/NB)

Communication & PR Assistant - Stage (6 mois) Janvier 2025 (F/H/NB)

Brand Manager Assistant - MARKETING DAY - Stage (6 mois) Janvier 2025 (F/N/NB)

Manufacturing Planning & Products Development Assistant - Stage (6 mois) Janvier 2025 (H/F/NB)

Retail Analyst & Sales Administration Assistant - Stage (6 mois) Janvier 2025 (H/F/NB)

UI Designer Assistant - Stage (6 mois) Janvier 2025 (F/M/NB)

Esports Communication Assistant

Machine Learning Engineer Assistant – Stage (6 mois) Janvier/Mars 2025 (F/H/NB)

Social Media Assistant – Stage (6 mois) Janvier 2025 (F/H/NB)

[flexispheres]

Educator – IOM Greece (Patras)

Position Title: Educator Duty Station: Patras, Greece Type of Appointment: Special Short-Term, Ungraded (up to 9 months) Job Schedule: Full-time, Day Shift Application Deadline: 5 June 2025, 20:59 (local time) Job ID: 14007 Recruitment Type: General Service (Local Recruitment Only) Empowering Young Lives: Become an Educator at IOM Greece Are you passionate about education and social inclusion? Do…

[puckpocketed]

Hello. You might have seen this floating around on twt:

link 1 // link 2, archive link

If by any chance you or someone you know are thinking about joining in on the challenge… no one can stop you but I implore you as someone who makes art, as someone with friends in an often-exploited creative industry, as someone who lives in late stage capitalism alongside you and has seen this play out before: proceed with caution.

Read the fine print on that form. There is NO guarantee of an internship, much less a job at the end of it. I haven't gone further than this form, but if anyone reading this does, and if there's no written agreement that your work won't be used without credit to you + payment for services rendered - RUN.

This is a common corporate tactic to get free labor out of people. I'm not saying this is necessarily what’s happening; for all we know this was done as a completely innocent move to drum up some fan engagement and as a genuine search for talent for their analytics team. WHO KNOWS. But I can't ignore that I’ve seen this situation play out again and again, at every scale.

Job interviews, when they ask you how YOU think they should improve their systems, how YOU would solve their problems? When they require that you do some problem-solving for them, and it goes beyond a simple task? That’s a free consultation you’re giving them, that's free work you or someone else should be getting paid for.

When big streamers/influencers ask their fans to join in on a fan art contest to choose their new pfp/banner? That’s hundreds, possibly thousands of pieces of free art they never would’ve gotten otherwise. They could've gone to the trouble of paying someone in-house to do it, hiring someone for that position, commissioning a professional for a piece. It's free work from their dedicated fans.

In this case, Utah HC is asking fans to not only choose/provide their own dataset, but to do a complex analysis on it AND do the work of visual and verbal communication to senior management, who likely do not have a deeper grasp of the concepts and will need it simplified. The stipulation that you will present your work could be ANYTHING!! The "five page deliverable" is already bananas to me, having dipped my toe into what analytics is and how complex the fun ones are. Condensing it all is WORK. The presentation portion may include speaking time and answering questions; the groundwork for doing this effectively may include producing data visualisations, making spreadsheets, time consuming write-ups. Maths and science communication is hard. It is WORK. They are asking for free labor.

Many have already called it out, but it's still gaining traction via retweets from big accounts uncritically sharing it. I found out through the official Puckpedia account. Jack Han called it out pretty eloquently on twitter and on his substack:

Many people aspire to work as an analyst in the NHL. Earlier today the Utah Hockey Club gave those people a glimmer of hope. Utah’s Summer Analytics Challenge is unusual in that it doesn’t provide a dataset or detailed instructions. The open-ended contests contrasts with other public (ex: Big Data Cup) or private (ex: NHL team interview) events. In those scenarios, participants are given proprietary data to clean, model and analyze, which influence direction and methodology. Meanwhile, Utah is seemingly happy with anything as long as the writeup is under five pages long. Utah’s contest also stands out in its near-total absence of legal fine print. There are no mention of intellectual property implications, which is perhaps fitting when the team is asking participants to bring their own data and analysis. [...] Open casting calls such as Utah’s analytics challenge start out as a lose-lose-lose proposition: > The employer loses because it will have to invest massive human resources to trawl/filter/evaluate/reverse-engineer the hundreds of write-ups it is sure to receive, with no guarantee that any of them will be of use > Applicants lose because the vast, vast majority of them will have nothing to show for their efforts, while a tiny minority risks having its IP stolen > Good ideas lose because they’ll be born into an environment where their parents (the applicant & the employer) have no defined relationship and won’t be in a position to grow together

link, archive link

I do try to keep things light on this blog, but this is super personal for me <3 thank u for listening

[veris-studies]

26/06/2025 | Thursday

yesterday's exam went well! i didn't bother tracking the time i spent revising though, since i knew i wouldn't be procrastinating on the exam day, lol.

my internship supervisor hasnt yet informed me of my next steps, so i spent my time today figuring out a roadmap for getting into a data analyst role. my biggest learning goals for this year are to learn ms excel in depth and get more practical knowledge of sql. seems like my college course skipped over some key concepts 🫠

i also spent an hour on a machine learning course im taking for my honours. and finally, i did a 20min workout.

[nasstechnologiesnagpur]

https://nasstechnologies.com/data-analyst.aspx