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Data Science Jobs
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𝗪𝗮𝗻𝘁 𝘁𝗼 𝗕𝘂𝗶𝗹𝗱 𝗮 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗣𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼 𝗧𝗵𝗮𝘁 𝗚𝗲𝘁𝘀 𝗬𝗼𝘂 𝗛𝗶𝗿𝗲𝗱?😍

If you’re just starting out in data analytics and wondering how to stand out — real-world projects are the key📊

No recruiter is impressed by “just theory.” What they want to see? Actionable proof of your skills👨‍💻📌

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4ezeIc9

Show recruiters that you don’t just “know” tools — you use them to solve problems✅️
𝐉𝐮𝐧𝐢𝐨𝐫 𝐯𝐬. 𝐒𝐞𝐧𝐢𝐨𝐫 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐭

What’s the real difference between Junior and Senior Data Analyst?

It’s not just SQL skills or years on the job — it’s how they think.

📚Juniors code right away
🧠Seniors figure out the problem first
Example: Juniors query without asking, Seniors check the goal.

📚Juniors follow orders
🧠Seniors ask questions
Example: Juniors build blindly, Seniors confirm metrics.

📚Juniors patch data
🧠Seniors fix the source
Example: Juniors fill gaps, Seniors debug the ETL.

📚Juniors stall in chaos
🧠Seniors make a plan
Example: Juniors wait, Seniors step up.

📚Juniors focus on tasks
🧠Seniors see the big picture
Example: Juniors report, Seniors connect to goals.

📚Juniors guess
🧠Seniors clarify
Example: Juniors assume, Seniors ask the team.

📚Juniors stick to old tools
🧠Seniors try new ones
Example: Juniors love Excel, Seniors code in Python.

📚Juniors give data
🧠Seniors give insights
Example: Juniors share stats, Seniors spot trends.


Seniority is about mindset, not just time.
3
𝗪𝗮𝗻𝘁 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗜𝗻-𝗗𝗲𝗺𝗮𝗻𝗱 𝗧𝗲𝗰𝗵 𝗦𝗸𝗶𝗹𝗹𝘀 — 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 — 𝗗𝗶𝗿𝗲𝗰𝘁𝗹𝘆 𝗳𝗿𝗼𝗺 𝗚𝗼𝗼𝗴𝗹𝗲?😍

Whether you’re a student, job seeker, or just hungry to upskill — these 5 beginner-friendly courses are your golden ticket🎟️

No fluff. No fees. Just career-boosting knowledge and certificates that make your resume pop✨️

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/42vL6br

Enjoy Learning ✅️
1
𝗟𝗲𝗮𝗿𝗻 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 (𝗡𝗼 𝗦𝘁𝗿𝗶𝗻𝗴𝘀 𝗔𝘁𝘁𝗮𝗰𝗵𝗲𝗱)

𝗡𝗼 𝗳𝗮𝗻𝗰𝘆 𝗰𝗼𝘂𝗿𝘀𝗲𝘀, 𝗻𝗼 𝗰𝗼𝗻𝗱𝗶𝘁𝗶𝗼𝗻𝘀, 𝗷𝘂𝘀𝘁 𝗽𝘂𝗿𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴.

𝗛𝗲𝗿𝗲’𝘀 𝗵𝗼𝘄 𝘁𝗼 𝗯𝗲𝗰𝗼𝗺𝗲 𝗮 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘:

1️⃣ Python Programming for Data Science → Harvard’s CS50P
The best intro to Python for absolute beginners:
↬ Covers loops, data structures, and practical exercises.
↬ Designed to help you build foundational coding skills.

Link: https://cs50.harvard.edu/python/

https://news.1rj.ru/str/datasciencefun

2️⃣ Statistics & Probability → Khan Academy
Want to master probability, distributions, and hypothesis testing? This is where to start:
↬ Clear, beginner-friendly videos.
↬ Exercises to test your skills.

Link: https://www.khanacademy.org/math/statistics-probability

https://whatsapp.com/channel/0029Vat3Dc4KAwEcfFbNnZ3O

3️⃣ Linear Algebra for Data Science → 3Blue1Brown
↬ Learn about matrices, vectors, and transformations.
↬ Essential for machine learning models.

Link: https://www.youtube.com/playlist?list=PLZHQObOWTQDMsr9KzVk3AjplI5PYPxkUr

4️⃣ SQL Basics → Mode Analytics
SQL is the backbone of data manipulation. This tutorial covers:
↬ Writing queries, joins, and filtering data.
↬ Real-world datasets to practice.

Link: https://mode.com/sql-tutorial

https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v

5️⃣ Data Visualization → freeCodeCamp
Learn to create stunning visualizations using Python libraries:
↬ Covers Matplotlib, Seaborn, and Plotly.
↬ Step-by-step projects included.

Link: https://www.youtube.com/watch?v=JLzTJhC2DZg

https://whatsapp.com/channel/0029VaxaFzoEQIaujB31SO34

6️⃣ Machine Learning Basics → Google’s Machine Learning Crash Course
An in-depth introduction to machine learning for beginners:
↬ Learn supervised and unsupervised learning.
↬ Hands-on coding with TensorFlow.

Link: https://developers.google.com/machine-learning/crash-course

7️⃣ Deep Learning → Fast.ai’s Free Course
Fast.ai makes deep learning easy and accessible:
↬ Build neural networks with PyTorch.
↬ Learn by coding real projects.

Link: https://course.fast.ai/

8️⃣ Data Science Projects → Kaggle
↬ Compete in challenges to practice your skills.
↬ Great way to build your portfolio.

Link: https://www.kaggle.com/
2
𝗛𝗮𝗿𝘃𝗮𝗿𝗱 𝗝𝘂𝘀𝘁 𝗥𝗲𝗹𝗲𝗮𝘀𝗲𝗱 𝟱 𝗙𝗥𝗘𝗘 𝗧𝗲𝗰𝗵 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻’𝘁 𝗠𝗶𝘀𝘀 𝗶𝗻 𝟮𝟬𝟮𝟱!😍

🚨 Harvard just dropped 5 FREE online tech courses — no fees, no catches!📌

Whether you’re just starting out or upskilling for a tech career, this is your chance to learn from one of the world’s top universities — for FREE. 🌍

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4eA368I

💡Learn at your own pace, earn certificates, and boost your resume✅️
1
If you are interested to learn SQL for data analytics purpose and clear the interviews, just cover the following topics

1)Install MYSQL workbench
2) Select
3) From
4) where
5) group by
6) having
7) limit
8) Joins (Left, right , inner, self, cross)
9) Aggregate function ( Sum, Max, Min , Avg)
9) windows function ( row num, rank, dense rank, lead, lag, Sum () over)
10)Case
11) Like
12) Sub queries
13) CTE
14) Replace CTE with temp tables
15) Methods to optimize Sql queries
16) Solve problems and case studies at Ankit Bansal youtube channel

Trick: Just copy each term and paste on youtube and watch any 10 to 15 minute on each topic and practise it while learning , By doing this , you get the basics understanding

17) Now time to go on youtube and search data analysis end to end project using sql

18) Watch them and practise them end to end.

17) learn integration with power bi

In this way , you will not only memorize the concepts but also learn how to implement them in your current working and projects and will be able to defend it in your interviews as well.

Like for more

Here you can find essential SQL Interview Resources👇
https://news.1rj.ru/str/DataSimplifier

Hope it helps :)
2
Forwarded from Python for Data Analysts
𝗨𝗽𝘀𝗸𝗶𝗹𝗹 𝗙𝗮𝘀𝘁: 𝗟𝗲𝗮𝗿𝗻 𝗧𝗲𝗰𝗵 𝗦𝗸𝗶𝗹𝗹𝘀 𝘄𝗶𝘁𝗵 𝗣𝗿𝗼𝗷𝗲𝗰𝘁-𝗕𝗮𝘀𝗲𝗱 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗶𝗻 𝗝𝘂𝘀𝘁 𝟯𝟬 𝗗𝗮𝘆𝘀!😍

Level up your tech skills in just 30 days! 💻👨‍🎓

Whether you’re a beginner, student, or planning a career switch, this platform offers project-based courses👨‍💻✨️

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/3U2nBl4

Start today and you’ll be 10x more confident by the end of it!✅️
2
2 VERY IMPORTANT MISAKES to avoid for job seekers
Trying or struggling to get Interview Calls

Let me summarise.

Many job applicants for analytics roles (also applicable for other roles) often get frustrated with receiving no interview calls DESPITE putting a lot of good projects, certifications and even their prior experience.

There are probably 2 key yet common mistakes you could be making during your application:

𝟏. 𝐘𝐨𝐮𝐫 𝐑𝐞𝐬𝐮𝐦𝐞 𝐈𝐬𝐧'𝐭 𝐓𝐚𝐢𝐥𝐨𝐫𝐞𝐝 𝐅𝐨𝐫 𝐓𝐡𝐞 𝐑𝐨𝐥𝐞
- Companies use an ATS to scan for relevant profiles amongst 100 of applications based on finding relevant key words.
- Ensure you update your resume to include the skills they're looking for.
- This will increase the chance of the ATS picking up on your resume.

𝟐. 𝐁𝐮𝐢𝐥𝐝 𝐘𝐨𝐮𝐫 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 𝐏𝐫𝐨𝐟𝐢𝐥𝐞 & 𝐀𝐜𝐭𝐢𝐯𝐢𝐭𝐲- - - - - If your resume reaches the technical/hiring team - they'll want to get more information about you.
- Their Next Stop - YOUR LINKEDIN PROFILE
- Update your certifications/skills & upload your key projects.
- Be Active and Share Your Learnings.
- This builds your credibility in their eyes

Remember....
You're competing against large pool of equally or more talented individuals like yourself.

On A Technical And Accomplishment level, you might on par with others.

Then it goes down to who can stand out from the rest.

Luck can play a huge role, but so can being strategic in your application.

Leave no stone unturned.

Join our WhatsApp channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
3
Forwarded from Python for Data Analysts
𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁’𝘀 𝗙𝗥𝗘𝗘 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 𝗖𝗼𝘂𝗿𝘀𝗲 – 𝗟𝗲𝗮𝗿𝗻 𝗛𝗼𝘄 𝘁𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗔𝗜 𝗪𝗼𝗿𝗸𝘀😍

🚨 Microsoft just dropped a brand-new FREE course on AI Agents — and it’s a must-watch!📲

If you’ve ever wondered how AI copilots, autonomous agents, and decision-making systems actually work👨‍🎓💫

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4kuGLLe

This course is your launchpad into the future of artificial intelligence✅️
2
Essential Topics to Master Data Analytics Interviews: 🚀

SQL:
1. Foundations
- SELECT statements with WHERE, ORDER BY, GROUP BY, HAVING
- Basic JOINS (INNER, LEFT, RIGHT, FULL)
- Navigate through simple databases and tables

2. Intermediate SQL
- Utilize Aggregate functions (COUNT, SUM, AVG, MAX, MIN)
- Embrace Subqueries and nested queries
- Master Common Table Expressions (WITH clause)
- Implement CASE statements for logical queries

3. Advanced SQL
- Explore Advanced JOIN techniques (self-join, non-equi join)
- Dive into Window functions (OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, lead, lag)
- Optimize queries with indexing
- Execute Data manipulation (INSERT, UPDATE, DELETE)

Python:
1. Python Basics
- Grasp Syntax, variables, and data types
- Command Control structures (if-else, for and while loops)
- Understand Basic data structures (lists, dictionaries, sets, tuples)
- Master Functions, lambda functions, and error handling (try-except)
- Explore Modules and packages

2. Pandas & Numpy
- Create and manipulate DataFrames and Series
- Perfect Indexing, selecting, and filtering data
- Handle missing data (fillna, dropna)
- Aggregate data with groupby, summarizing data
- Merge, join, and concatenate datasets

3. Data Visualization with Python
- Plot with Matplotlib (line plots, bar plots, histograms)
- Visualize with Seaborn (scatter plots, box plots, pair plots)
- Customize plots (sizes, labels, legends, color palettes)
- Introduction to interactive visualizations (e.g., Plotly)

Excel:
1. Excel Essentials
- Conduct Cell operations, basic formulas (SUMIFS, COUNTIFS, AVERAGEIFS, IF, AND, OR, NOT & Nested Functions etc.)
- Dive into charts and basic data visualization
- Sort and filter data, use Conditional formatting

2. Intermediate Excel
- Master Advanced formulas (V/XLOOKUP, INDEX-MATCH, nested IF)
- Leverage PivotTables and PivotCharts for summarizing data
- Utilize data validation tools
- Employ What-if analysis tools (Data Tables, Goal Seek)

3. Advanced Excel
- Harness Array formulas and advanced functions
- Dive into Data Model & Power Pivot
- Explore Advanced Filter, Slicers, and Timelines in Pivot Tables
- Create dynamic charts and interactive dashboards

Power BI:
1. Data Modeling in Power BI
- Import data from various sources
- Establish and manage relationships between datasets
- Grasp Data modeling basics (star schema, snowflake schema)

2. Data Transformation in Power BI
- Use Power Query for data cleaning and transformation
- Apply advanced data shaping techniques
- Create Calculated columns and measures using DAX

3. Data Visualization and Reporting in Power BI
- Craft interactive reports and dashboards
- Utilize Visualizations (bar, line, pie charts, maps)
- Publish and share reports, schedule data refreshes

Statistics Fundamentals:
- Mean, Median, Mode
- Standard Deviation, Variance
- Probability Distributions, Hypothesis Testing
- P-values, Confidence Intervals
- Correlation, Simple Linear Regression
- Normal Distribution, Binomial Distribution, Poisson Distribution.

Show some ❤️ if you're ready to elevate your data analytics journey! 📊

ENJOY LEARNING 👍👍
3
📌AstraZeneca is hiring for Data Scientist Role
Experience: 0 - 2 year's
Apply here:
https://careers.astrazeneca.com/job/-/-/7684/78581782656

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

👉 Telegram Channel: https://news.1rj.ru/str/addlist/4q2PYC0pH_VjZDk5

All the best! 👍👍
𝗪𝗶𝗽𝗿𝗼’𝘀 𝗙𝗿𝗲𝗲 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗔𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗼𝗿: 𝗬𝗼𝘂𝗿 𝗙𝗮𝘀𝘁-𝗧𝗿𝗮𝗰𝗸 𝘁𝗼 𝗮 𝗗𝗮𝘁𝗮 𝗖𝗮𝗿𝗲𝗲𝗿!😍

Want to break into Data Science but don’t have a degree or years of experience? Wipro just made it easier than ever!👨‍🎓✨️

With the Wipro Data Science Accelerator, you can start learning for FREE—no fancy credentials needed. Whether you’re a beginner or an aspiring data professional👨‍💻📌

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4hOXcR7

Ready to start? Explore Wipro’s Data Science Accelerator here✅️
1
UiPath is hiring Machine Learning Engineer

For 2022, 2023, 2024, 2025 grads
Location: Jaipur

https://jobs.ashbyhq.com/uipath/72b31ba5-168c-4edc-983a-e9a9a0c508c8

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

👉 Telegram Channel: https://news.1rj.ru/str/addlist/4q2PYC0pH_VjZDk5

All the best! 👍👍
𝗛𝗶𝗱𝗱𝗲𝗻 𝗚𝗲𝗺 𝗳𝗼𝗿 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗿𝗼𝗺 𝗠𝗜𝗧, 𝗛𝗮𝗿𝘃𝗮𝗿𝗱 & 𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱!😍

Still searching for quality learning resources?📚

What if I told you there’s a platform offering free full-length courses from top universities like MIT, Stanford, and Harvard — and most people have never even heard of it? 🤯

𝗟𝗶𝗻𝗸𝘀:-👇

https://pdlink.in/4lN7aF1

Don’t skip this chance✅️
1
🔍 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 ❤️
1
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
2
Forwarded from Python for Data Analysts
𝗪𝗮𝗻𝘁 𝘁𝗼 𝗣𝗿𝗼𝘃𝗲 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗦𝗸𝗶𝗹𝗹𝘀 𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝗦𝗽𝗲𝗻𝗱𝗶𝗻𝗴 𝗮 𝗥𝘂𝗽𝗲𝗲?😍

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.📚💫

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4eNiUVP

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
1
Atlassian is hiring Machine Learning Engineer

For 2021, 2022, 2023 grads
Location: Bangalore

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