🔍 Best Data Analytics Roles Based on Your Graduation Background!

Thinking about a career in Data Analytics but unsure which role fits your background? Check out these top job roles based on your degree:

🚀 For Mathematics/Statistics Graduates:
🔹 Data Analyst
🔹 Statistical Analyst
🔹 Quantitative Analyst
🔹 Risk Analyst

🚀 For Computer Science/IT Graduates:
🔹 Data Scientist
🔹 Business Intelligence Developer
🔹 Data Engineer
🔹 Data Architect

🚀 For Economics/Finance Graduates:
🔹 Financial Analyst
🔹 Market Research Analyst
🔹 Economic Consultant
🔹 Data Journalist

🚀 For Business/Management Graduates:
🔹 Business Analyst
🔹 Operations Research Analyst
🔹 Marketing Analytics Manager
🔹 Supply Chain Analyst

🚀 For Engineering Graduates:
🔹 Data Scientist
🔹 Industrial Engineer
🔹 Operations Research Analyst
🔹 Quality Engineer

🚀 For Social Science Graduates:
🔹 Data Analyst
🔹 Research Assistant
🔹 Social Media Analyst
🔹 Public Health Analyst

🚀 For Biology/Healthcare Graduates:
🔹 Clinical Data Analyst
🔹 Biostatistician
🔹 Research Coordinator
🔹 Healthcare Consultant

✅ Pro Tip:

Some of these roles may require additional certifications or upskilling in SQL, Python, Power BI, Tableau, or Machine Learning to stand out in the job market.

Like if it helps ❤️

Data Engineering Roles @ MathCo! 🚨

We're building cutting-edge solutions across cloud, data, and product ecosystems—and we’re looking for exceptional talent to join our growing engineering team.
If you're excited by real-world impact, solving complex data problems, and working alongside some of the sharpest minds in the industry, let’s connect.

Open Roles:

1. Cloud Engineer – II
Design and manage cloud-native data infrastructure, optimize pipelines, and solve complex ETL challenges using SQL and modern cloud platforms.

2. Senior Data Engineer
Lead PoCs/PoVs and scale reliable data systems across cloud, batch, and real-time architectures.

3. Lead Data Engineer
Architect scalable pipelines, collaborate with cross-functional teams, and lead delivery of end-to-end, business-aligned solutions.

4. Engineering Manager
Drive strategy, mentor high-performing teams, and lead the delivery of high-impact outcomes across the modern data stack.

📍Location: Bangalore

📩 Interested? Drop your CV at arvind.pothula@mathco.com

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Knowledge is powerful — but certifications show proof. Whether you’re applying for internships, jobs, or freelance roles, having verifiable credentials in Python, SQL, and Data Visualization can set you apart.📚💫

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Enjoy Learning ✅️

The Only SQL You Actually Need For Your First Job (Data Analytics)

The Learning Trap: What Most Beginners Fall Into

When starting out, it's common to feel like you need to master every possible SQL concept. You binge YouTube videos, tutorials, and courses, yet still feel lost in interviews or when given a real dataset.

Common traps:

- Complex subqueries

- Advanced CTEs

- Recursive queries

- 100+ tutorials watched

- 0 practical experience


Reality Check: What You'll Actually Use 75% of the Time

Most data analytics roles (especially entry-level) require clarity, speed, and confidence with core SQL operations. Here’s what covers most daily work:

1. SELECT, FROM, WHERE — The Foundation

SELECT name, age
FROM employees
WHERE department = 'Finance';

This is how almost every query begins. Whether exploring a dataset or building a dashboard, these are always in use.

2. JOINs — Combining Data From Multiple Tables

SELECT e.name, d.department_name
FROM employees e
JOIN departments d ON e.department_id = d.id;

You’ll often join tables like employee data with department, customer orders with payments, etc.

3. GROUP BY — Summarizing Data

SELECT department, COUNT(*) AS employee_count
FROM employees
GROUP BY department;

Used to get summaries by categories like sales per region or users by plan.

4. ORDER BY — Sorting Results

SELECT name, salary
FROM employees
ORDER BY salary DESC;

Helps sort output for dashboards or reports.

5. Aggregations — Simple But Powerful

Common functions: COUNT(), SUM(), AVG(), MIN(), MAX()

SELECT AVG(salary)
FROM employees
WHERE department = 'IT';

Gives quick insights like average deal size or total revenue.

6. ROW_NUMBER() — Adding Row Logic

SELECT *
FROM (
SELECT *, ROW_NUMBER() OVER(PARTITION BY customer_id ORDER BY order_date DESC) as rn
FROM orders
) sub
WHERE rn = 1;

Used for deduplication, rankings, or selecting the latest record per group.

Credits: https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02

React ❤️ for more

Atlassian hiring Data Engineer

Apply link: https://careers-apac-atlassian.icims.com/jobs/19687/data-engineer/job?iis=LinkedIn&iisn=LinkedIn_Job_Ad

Atlassian is hiring Machine Learning Engineer

For 2021, 2022, 2023 grads
Location: Bangalore

https://www.atlassian.com/company/careers

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Data Science Learning Plan

Step 1: Mathematics for Data Science (Statistics, Probability, Linear Algebra)

Step 2: Python for Data Science (Basics and Libraries)

Step 3: Data Manipulation and Analysis (Pandas, NumPy)

Step 4: Data Visualization (Matplotlib, Seaborn, Plotly)

Step 5: Databases and SQL for Data Retrieval

Step 6: Introduction to Machine Learning (Supervised and Unsupervised Learning)

Step 7: Data Cleaning and Preprocessing

Step 8: Feature Engineering and Selection

Step 9: Model Evaluation and Tuning

Step 10: Deep Learning (Neural Networks, TensorFlow, Keras)

Step 11: Working with Big Data (Hadoop, Spark)

Step 12: Building Data Science Projects and Portfolio

Data Science Resources
👇👇
https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y

Like for more 😄

1: How would you preprocess and tokenize text data from tweets for sentiment analysis? Discuss potential challenges and solutions.

- Answer: Preprocessing and tokenizing text data for sentiment analysis involves tasks like lowercasing, removing stop words, and stemming or lemmatization. Handling challenges like handling emojis, slang, and noisy text is crucial. Tools like NLTK or spaCy can assist in these tasks.


2: Explain the collaborative filtering approach in building recommendation systems. How might Twitter use this to enhance user experience?

- Answer: Collaborative filtering recommends items based on user preferences and similarities. Techniques include user-based or item-based collaborative filtering and matrix factorization. Twitter could leverage user interactions to recommend tweets, users, or topics.


3: Write a Python or Scala function to count the frequency of hashtags in a given collection of tweets.

- Answer (Python):

     def count_hashtags(tweet_collection):
         hashtags_count = {}
         for tweet in tweet_collection:
             hashtags = [word for word in tweet.split() if word.startswith('#')]
             for hashtag in hashtags:
                 hashtags_count[hashtag] = hashtags_count.get(hashtag, 0) + 1
         return hashtags_count
     

4: How does graph analysis contribute to understanding user interactions and content propagation on Twitter? Provide a specific use case.

- Answer: Graph analysis on Twitter involves examining user interactions. For instance, identifying influential users or detecting communities based on retweet or mention networks. Algorithms like PageRank or Louvain Modularity can aid in these analyses.

𝟲 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗦𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 & 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗝𝗼𝘂𝗿𝗻𝗲𝘆😍

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This list will set you up with real-world, job-ready skills✅️

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Your dream job might just start here.✅️

The job search journey can be tough, but every step you take brings you closer to your goal. Customizing resumes and cover letters, practicing coding challenges, and staying on top of industry trends are all part of the path to success. Remember, you only need one "yes" to change everything.

There are a lot of amazing people out there looking for that one opportunity. Every application you send, every new connection you make, and all those late nights spent refining your portfolio or building professional relationships are steps toward landing the right job. It can be really exhausting, but every bit of effort gets you closer to your goal.

The process can be filled with doubts and uncertainties, but having a structured approach and setting daily goals can help manage it. Joining professional groups, attending webinars, and seeking mentorship are also great ways to gain insights and stay motivated.

In the end, all the time and energy you invest—whether it’s perfecting a project, learning a new tool, or reaching out to potential mentors—pays off. So, if you’re looking for a job, keep learning, applying, and networking.

Zelestra is hiring Junior Data Scientist 🚀

Experience : 0-2 Years
Location : Gurugram

Apply link : https://careers.zelestra.energy/job/Haryana-Junior-Data-Scientist/1162773055/

👉 WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226

👉 Telegram Channel: https://t.me/addlist/4q2PYC0pH_VjZDk5

All the best! 👍👍

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Level up your career in the booming field of data✅️

United Airlines is hiring Associate Analyst 🚀

Experience : 0-2 Years
Location : Gurugram

Apply link : https://careers.united.com/us/en/job/UAIUADUSGGN00002147EXTERNALENUSTALEO/Associate-Analyst-Customer-Insights-Analytics-IKC?utm_source=linkedin&utm_medium=phenom-feeds

👉 WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226

👉 Telegram Channel: https://t.me/addlist/4q2PYC0pH_VjZDk5

All the best! 👍👍

Deloitte is hiring Data Analyst 🚀

Experience : 1+ Year
Location : Chennai

Apply link : https://www.linkedin.com/jobs/view/4267803159

👉 WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226

👉 Telegram Channel: https://t.me/addlist/4q2PYC0pH_VjZDk5

All the best! 👍👍