Data Analyst Interview Resources
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โœ… Data Analytics Roadmap for Freshers ๐Ÿš€๐Ÿ“Š

1๏ธโƒฃ Understand What a Data Analyst Does
๐Ÿ” Analyze data, find insights, create dashboards, support business decisions.

2๏ธโƒฃ Start with Excel
๐Ÿ“ˆ Learn:
โ€“ Basic formulas
โ€“ Charts & Pivot Tables
โ€“ Data cleaning
๐Ÿ’ก Excel is still the #1 tool in many companies.

3๏ธโƒฃ Learn SQL
๐Ÿงฉ SQL helps you pull and analyze data from databases.
Start with:
โ€“ SELECT, WHERE, JOIN, GROUP BY
๐Ÿ› ๏ธ Practice on platforms like W3Schools or Mode Analytics.

4๏ธโƒฃ Pick a Programming Language
๐Ÿ Start with Python (easier) or R
โ€“ Learn pandas, matplotlib, numpy
โ€“ Do small projects (e.g. analyze sales data)

5๏ธโƒฃ Data Visualization Tools
๐Ÿ“Š Learn:
โ€“ Power BI or Tableau
โ€“ Build simple dashboards
๐Ÿ’ก Start with free versions or YouTube tutorials.

6๏ธโƒฃ Practice with Real Data
๐Ÿ” Use sites like Kaggle or Data.gov
โ€“ Clean, analyze, visualize
โ€“ Try small case studies (sales report, customer trends)

7๏ธโƒฃ Create a Portfolio
๐Ÿ’ป Share projects on:
โ€“ GitHub
โ€“ Notion or a simple website
๐Ÿ“Œ Add visuals + brief explanations of your insights.

8๏ธโƒฃ Improve Soft Skills
๐Ÿ—ฃ๏ธ Focus on:
โ€“ Presenting data in simple words
โ€“ Asking good questions
โ€“ Thinking critically about patterns

9๏ธโƒฃ Certifications to Stand Out
๐ŸŽ“ Try:
โ€“ Google Data Analytics (Coursera)
โ€“ IBM Data Analyst
โ€“ LinkedIn Learning basics

๐Ÿ”Ÿ Apply for Internships & Entry Jobs
๐ŸŽฏ Titles to look for:
โ€“ Data Analyst (Intern)
โ€“ Junior Analyst
โ€“ Business Analyst

๐Ÿ’ฌ React โค๏ธ for more!
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๐Ÿš€ 5 Frequently Asked SQL Interview Q&A ๐Ÿ’ป๐Ÿ“Š

1๏ธโƒฃ Difference between RANK() and DENSE_RANK()?

โœ… RANK() skips numbers after ties
โœ… DENSE_RANK() does not skip numbers

Example: 95, 95, 90
RANK() โ†’ 1,1,3
DENSE_RANK() โ†’ 1,1,2

โ€”

2๏ธโƒฃ What is a Window Function?

๐Ÿ“ˆ Performs calculations across rows without grouping them into one row.

Examples:
โœ”๏ธ ROW_NUMBER()
โœ”๏ธ RANK()
โœ”๏ธ LEAD()
โœ”๏ธ LAG()

โ€”

3๏ธโƒฃ ROW_NUMBER() vs RANK()?

๐Ÿ”ข ROW_NUMBER() gives unique numbers to every row.
๐Ÿ”ข RANK() gives same rank to duplicate values.

โ€”

4๏ธโƒฃ What is a Stored Procedure?

โš™๏ธ A saved SQL query that can be reused anytime.

Benefits:
โœ… Reusable
โœ… Faster execution
โœ… Better security

โ€”

5๏ธโƒฃ WHERE vs GROUP BY?

๐Ÿ“Œ WHERE filters rows
๐Ÿ“Œ GROUP BY groups rows for aggregation

๐Ÿ”ฅ React for more interview questions โ™ฅ๏ธ
โค6
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๐Ÿง  Advance SQL Interview Question โšก

๐Ÿ“Š Find the department with the highest total salary expense

Table: Employees

Columns:

employee_id , employee_name , department_id , salary

๐Ÿ” Query:

WITH dept_salary AS (
SELECT department_id,
SUM(salary) AS total_salary
FROM Employees
GROUP BY department_id
)

SELECT department_id,
total_salary
FROM dept_salary
WHERE total_salary = (
SELECT MAX(total_salary)
FROM dept_salary
);

๐ŸŽฏ Why this question matters:

โœ… Tests CTE + aggregation concepts
โœ… Evaluates nested subquery understanding

๐Ÿš€ Pro Tip:

Using a CTE first makes complex aggregate queries much cleaner and easier to debug.

๐Ÿ”ฅ React โค๏ธ for more advanced SQL interview questions ๐Ÿš€
โœ… Top Data Analyst Interview Q&A ๐ŸŽฏ

1. How do you handle messy or incomplete data in a real project
Answer:
I start by profiling the dataset to identify missing values, duplicates, and inconsistent formats. Depending on the context, I may impute missing values using mean/median, flag them for review, or exclude them if theyโ€™re not critical. For example, in an HR dataset, I used pandas to standardize date formats and fill missing department fields based on role titles.

2. Describe a time you built a dashboard that influenced a business decision
Answer:
At my previous role, I built a Power BI dashboard to track churn across customer segments. It revealed that users from a specific region had a 30% higher churn rate. This insight led the marketing team to launch a targeted retention campaign, reducing churn by 12% in the next quarter.

3. How do you approach a vague business question like โ€œWhy are sales droppingโ€
Answer:
I break it down by segmenting dataโ€”region, product, time periodโ€”and look for anomalies or trends. I compare current vs. previous periods, analyze customer behavior, and check for external factors. In one case, I discovered that a drop in sales was due to a discontinued product line that hadnโ€™t been flagged in reporting.

4. Whatโ€™s your process for analyzing an A/B test
Answer:
I define the hypothesis, ensure randomization, and check sample sizes. Then I compare metrics like conversion rate between control and test groups using statistical tests (e.g., t-test or chi-square). I also calculate p-values and confidence intervals to determine significance. I once helped a product team validate a new checkout flow that increased conversions by 8%.

5. How do you ensure your analysis is understandable to non-technical stakeholders
Answer:
I focus on clarityโ€”use simple language, clean visuals, and highlight key takeaways. I avoid jargon and always tie insights to business impact. For example, instead of saying โ€œstandard deviation,โ€ I might say โ€œvariation in customer spending.โ€

6. What tools do you use for forecasting and how do you validate your predictions
Answer:
I use Excel for quick models and Pythonโ€™s statsmodels or Prophet for more robust forecasting. I validate predictions using historical data and metrics like RMSE or MAPE. In a recent project, I forecasted monthly sales and helped the inventory team reduce overstock by 15%.

7. How do you automate repetitive reporting tasks
Answer:
I use Python scripts with scheduled jobs or Power BIโ€™s refresh features. In one case, I automated a weekly sales report using Google Sheets + Apps Script, saving 5 hours of manual work per week.

8. How do you prioritize multiple data requests from different teams
Answer:
I assess urgency, business impact, and effort required. I communicate clearly with stakeholders and use frameworks like ICE (Impact, Confidence, Effort) to align priorities. I also maintain a request tracker to manage expectations.

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๐Ÿง  Advanced SQL Interview Question โšก

๐Ÿ“Š Find pairs of employees who work in the same department and earn the same salary

Table: Employees

Columns:

employee_id, employee_name, department_id, salary

๐Ÿ” Query:

SELECT e1.employee_id AS emp1_id,
e1.employee_name AS emp1_name,
e2.employee_id AS emp2_id,
e2.employee_name AS emp2_name,
e1.department_id,
e1.salary
FROM Employees e1
JOIN Employees e2
ON e1.department_id = e2.department_id
AND e1.salary = e2.salary
AND e1.employee_id < e2.employee_id;

๐ŸŽฏ Why this question matters:

โœ… Tests self joins deeply
โœ… Evaluates logical thinking in SQL
โœ… Commonly asked in advanced interview rounds

๐Ÿš€ Pro Tip:

Self joins are extremely useful for comparing rows within the same table without using loops.

๐Ÿ”ฅ React โค๏ธ for more advanced SQL interview questions ๐Ÿš€
โค6
Data Analysis Interview Questions

1. What is the difference between Primary Key and Foreign Key? (SQL Basics)
2. Write a query to find the second highest salary in the Employee table.
3. How do you handle missing values in a dataset? (Data Cleaning)
4. What is the difference between COUNT(*), COUNT(column), and COUNT(DISTINCT column)?
5. What are measures of central tendency in statistics? (Stats Basics)
6. What is a window function in SQL? Provide examples of ROW_NUMBER and RANK.
7. Write a query to fetch the top 3 performing products based on sales.
8. Explain the difference between UNION and UNION ALL.
9. Explain p-value in hypothesis testing. (Statistics)
10. How would you detect outliers in a dataset? (EDA)
11. Write a query to get the top 3 departments with the highest average salary. (SQL + Aggregation)
12. What is correlation? How do you interpret it? (Statistics)
13. Explain the difference between DELETE and TRUNCATE commands.
14. What are KPIs? Give examples for an e-commerce company. (Business)
15. How do you calculate a running total in SQL? (Window Functions โ€“ Advanced SQL)
16. Explain the difference between Correlation and Regression. (Stats)
17. How do you handle imbalanced datasets in classification problems? (ML + Analytics)
18. How would you design an A/B test for a new pricing model? (Experiment Design)
19. How would you detect anomalies in financial transactions? (Real-World Case)


Data Analysis/Scenario-Based Questions

20. Write a query to identify the most profitable regions based on transaction data.
21. How would you analyze customer churn using SQL?
22. Explain the difference between OLAP and OLTP databases.
23. How would you determine the Average Revenue Per User (ARPU) from transaction data?
24. Describe a scenario where you would use a LEFT JOIN instead of an INNER JOIN.
25. Write a query to calculate YoY (Year-over-Year) growth for a set of transactions.
26. How would you implement fraud detection using transactional data?
27. Write a query to find customers who have used more than 2 credit cards for transactions in a given month.
28. How would you approach a business problem where you need to analyze the spending patterns of premium customers?
โค7
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SQL From Basic to Advanced level

Basic SQL is ONLY 7 commands:
- SELECT
- FROM
- WHERE (also use SQL comparison operators such as =, <=, >=, <> etc.)
- ORDER BY
- Aggregate functions such as SUM, AVERAGE, COUNT etc.
- GROUP BY
- CREATE, INSERT, DELETE, etc.
You can do all this in just one morning.

Once you know these, take the next step and learn commands like:
- LEFT JOIN
- INNER JOIN
- LIKE
- IN
- CASE WHEN
- HAVING (undertstand how it's different from GROUP BY)
- UNION ALL
This should take another day.

Once both basic and intermediate are done, start learning more advanced SQL concepts such as:
- Subqueries (when to use subqueries vs CTE?)
- CTEs (WITH AS)
- Stored Procedures
- Triggers
- Window functions (LEAD, LAG, PARTITION BY, RANK, DENSE RANK)
These can be done in a couple of days.
Learning these concepts is NOT hard at all

- what takes time is practice and knowing what command to use when. How do you master that?
- First, create a basic SQL project
- Then, work on an intermediate SQL project (search online) -

Lastly, create something advanced on SQL with many CTEs, subqueries, stored procedures and triggers etc.

This is ALL you need to become a badass in SQL, and trust me when I say this, it is not rocket science. It's just logic.

Remember that practice is the key here. It will be more clear and perfect with the continous practice

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Like this post if it helps ๐Ÿ˜„โค๏ธ

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โค1
๐— ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ผ๐—ณ๐˜ ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€๐ŸŽ“

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๐Ÿ“‚ Top Projects for Data Analytics Portfolio ๐Ÿš€๐Ÿ’ป

๐Ÿ“Š 1. Sales Dashboard (Excel / Power BI / Tableau)
โ–ถ๏ธ Analyze monthly/quarterly sales by region, category
โ–ถ๏ธ Show KPIs: Revenue, YoY Growth, Profit Margin

๐Ÿ› 2. E-commerce Customer Segmentation (Python + Clustering)
โ–ถ๏ธ Use RFM (Recency, Frequency, Monetary) model
โ–ถ๏ธ Visualize clusters with Seaborn / Plotly

๐Ÿ“‰ 3. Churn Prediction Model (Python + ML)
โ–ถ๏ธ Dataset: Telecom or SaaS customer data
โ–ถ๏ธ Techniques: Logistic Regression, Decision Tree

๐Ÿ“ฆ 4. Supply Chain Delay Analysis (SQL + Tableau)
โ–ถ๏ธ Identify causes of late deliveries using historical order data
โ–ถ๏ธ Visualize supplier-wise performance

๐Ÿ“ˆ 5. A/B Testing for Product Feature (SQL + Python)
โ–ถ๏ธ Simulate or use real test data (e.g. button click-through rates)
โ–ถ๏ธ Metrics: Conversion Rate, Significance Test

๐Ÿ“ 6. COVID-19 Trend Tracker (Python + Dash)
โ–ถ๏ธ Scrape or pull live data from APIs
โ–ถ๏ธ Show cases, recovery, testing rates by country

๐Ÿ“… 7. HR Analytics โ€“ Attrition Analysis (Excel / Python)
โ–ถ๏ธ Predict or explore employee exits
โ–ถ๏ธ Use decision trees or visual storytelling

๐Ÿ’ก Tip: Upload projects to GitHub + create a simple portfolio site or blog to stand out.

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โค10
๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐˜„๐—ถ๐˜๐—ต ๐—š๐—ฒ๐—ป๐—”๐—œ ๐—ข๐—ป๐—น๐—ถ๐—ป๐—ฒ ๐—ช๐—ฒ๐—ฏ๐—ถ๐—ป๐—ฎ๐—ฟ ๐Ÿ˜

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๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—ฅ๐—ผ๐—ฎ๐—ฑ๐—บ๐—ฎ๐—ฝ

๐Ÿญ. ๐—ฃ๐—ฟ๐—ผ๐—ด๐—ฟ๐—ฎ๐—บ๐—บ๐—ถ๐—ป๐—ด ๐—Ÿ๐—ฎ๐—ป๐—ด๐˜‚๐—ฎ๐—ด๐—ฒ๐˜€: Master Python, SQL, and R for data manipulation and analysis.

๐Ÿฎ. ๐——๐—ฎ๐˜๐—ฎ ๐— ๐—ฎ๐—ป๐—ถ๐—ฝ๐˜‚๐—น๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฎ๐—ป๐—ฑ ๐—ฃ๐—ฟ๐—ผ๐—ฐ๐—ฒ๐˜€๐˜€๐—ถ๐—ป๐—ด: Use Excel, Pandas, and ETL tools like Alteryx and Talend for data processing.

๐Ÿฏ. ๐——๐—ฎ๐˜๐—ฎ ๐—ฉ๐—ถ๐˜€๐˜‚๐—ฎ๐—น๐—ถ๐˜‡๐—ฎ๐˜๐—ถ๐—ผ๐—ป: Learn Tableau, Power BI, and Matplotlib/Seaborn for creating insightful visualizations.

๐Ÿฐ. ๐—ฆ๐˜๐—ฎ๐˜๐—ถ๐˜€๐˜๐—ถ๐—ฐ๐˜€ ๐—ฎ๐—ป๐—ฑ ๐— ๐—ฎ๐˜๐—ต๐—ฒ๐—บ๐—ฎ๐˜๐—ถ๐—ฐ๐˜€: Understand Descriptive and Inferential Statistics, Probability, Regression, and Time Series Analysis.

๐Ÿฑ. ๐— ๐—ฎ๐—ฐ๐—ต๐—ถ๐—ป๐—ฒ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ถ๐—ป๐—ด: Get proficient in Supervised and Unsupervised Learning, along with Time Series Forecasting.

๐Ÿฒ. ๐—•๐—ถ๐—ด ๐——๐—ฎ๐˜๐—ฎ ๐—ง๐—ผ๐—ผ๐—น๐˜€: Utilize Google BigQuery, AWS Redshift, and NoSQL databases like MongoDB for large-scale data management.

๐Ÿณ. ๐— ๐—ผ๐—ป๐—ถ๐˜๐—ผ๐—ฟ๐—ถ๐—ป๐—ด ๐—ฎ๐—ป๐—ฑ ๐—ฅ๐—ฒ๐—ฝ๐—ผ๐—ฟ๐˜๐—ถ๐—ป๐—ด: Implement Data Quality Monitoring (Great Expectations) and Performance Tracking (Prometheus, Grafana).

๐Ÿด. ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—ง๐—ผ๐—ผ๐—น๐˜€: Work with Data Orchestration tools (Airflow, Prefect) and visualization tools like D3.js and Plotly.

๐Ÿต. ๐—ฅ๐—ฒ๐˜€๐—ผ๐˜‚๐—ฟ๐—ฐ๐—ฒ ๐— ๐—ฎ๐—ป๐—ฎ๐—ด๐—ฒ๐—ฟ: Manage resources using Jupyter Notebooks and Power BI.

๐Ÿญ๐Ÿฌ. ๐——๐—ฎ๐˜๐—ฎ ๐—š๐—ผ๐˜ƒ๐—ฒ๐—ฟ๐—ป๐—ฎ๐—ป๐—ฐ๐—ฒ ๐—ฎ๐—ป๐—ฑ ๐—˜๐˜๐—ต๐—ถ๐—ฐ๐˜€: Ensure compliance with GDPR, Data Privacy, and Data Quality standards.

๐Ÿญ๐Ÿญ. ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—–๐—ผ๐—บ๐—ฝ๐˜‚๐˜๐—ถ๐—ป๐—ด: Leverage AWS, Google Cloud, and Azure for scalable data solutions.

๐Ÿญ๐Ÿฎ. ๐——๐—ฎ๐˜๐—ฎ ๐—ช๐—ฟ๐—ฎ๐—ป๐—ด๐—น๐—ถ๐—ป๐—ด ๐—ฎ๐—ป๐—ฑ ๐—–๐—น๐—ฒ๐—ฎ๐—ป๐—ถ๐—ป๐—ด: Master data cleaning (OpenRefine, Trifacta) and transformation techniques.

Data Analytics Resources
๐Ÿ‘‡๐Ÿ‘‡
https://t.me/sqlspecialist

Hope this helps you ๐Ÿ˜Š
โค4
๐—ง๐—ผ๐—ฝ ๐Ÿฏ ๐—™๐—ฅ๐—˜๐—˜ ๐—ฃ๐˜†๐˜๐—ต๐—ผ๐—ป ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—œ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ! ๐Ÿš€๐Ÿ’ป

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Data Analyst INTERVIEW QUESTIONS AND ANSWERS
๐Ÿ‘‡๐Ÿ‘‡

1.Can you name the wildcards in Excel?

Ans: There are 3 wildcards in Excel that can ve used in formulas.

Asterisk (*) โ€“ 0 or more characters. For example, Ex* could mean Excel, Extra, Expertise, etc.

Question mark (?) โ€“ Represents any 1 character. For example, R?ain may mean Rain or Ruin.

Tilde (~) โ€“ Used to identify a wildcard character (~, *, ?). For example, If you need to find the exact phrase India* in a list. If you use India* as the search string, you may get any word with India at the beginning followed by different characters (such as Indian, Indiana). If you have to look for Indiaโ€ exclusively, use ~.

Hence, the search string will be india~*. ~ is used to ensure that the spreadsheet reads the following character as is, and not as a wildcard.


2.What is cascading filter in tableau?

Ans: Cascading filters can also be understood as giving preference to a particular filter and then applying other filters on previously filtered data source. Right-click on the filter you want to use as a main filter and make sure it is set as all values in dashboard then select the subsequent filter and select only relevant values to cascade the filters. This will improve the performance of the dashboard as you have decreased the time wasted in running all the filters over complete data source.


3.What is the difference between .twb and .twbx extension?

Ans:
A .twb file contains information on all the sheets, dashboards and stories, but it wonโ€™t contain any information regarding data source. Whereas .twbx file contains all the sheets, dashboards, stories and also compressed data sources. For saving a .twbx extract needs to be performed on the data source. If we forward .twb file to someone else than they will be able to see the worksheets and dashboards but wonโ€™t be able to look into the dataset.


4.What are the various Power BI versions?

Power BI Premium capacity-based license, for example, allows users with a free license to act on content in workspaces with Premium capacity. A user with a free license can only use the Power BI service to connect to data and produce reports and dashboards in My Workspace outside of Premium capacity. They are unable to exchange material or publish it in other workspaces. To process material, a Power BI license with a free or Pro per-user license only uses a shared and restricted capacity. Users with a Power BI Pro license can only work with other Power BI Pro users if the material is stored in that shared capacity. They may consume user-generated information, post material to app workspaces, share dashboards, and subscribe to dashboards and reports. Pro users can share material with users who donโ€™t have a Power BI Pro subscription while workspaces are at Premium capacity.

ENJOY LEARNING ๐Ÿ‘๐Ÿ‘
โค1๐Ÿ‘1
๐Ÿš€Greetings from PVR Cloud Tech!! ๐ŸŒˆ

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โค1
Give me 5 minutes, I will tell you

7 ways to get your next job in 3 months.

The situation is tough and talking to your colleague or mentor wonโ€™t change a thing. Doing the below 6 things might get you your next opportunity faster

โœ… Save this post for future reference

๐Ÿญ. ๐—จ๐—ฝ๐—ฑ๐—ฎ๐˜๐—ฒ ๐—Ÿ๐—ถ๐—ป๐—ธ๐—ฒ๐—ฑ๐—œ๐—ป โ€˜๐—ข๐—ฝ๐—ฒ๐—ป ๐—ง๐—ผ ๐—ช๐—ผ๐—ฟ๐—ธโ€™ ๐—ฆ๐—ฒ๐˜๐˜๐—ถ๐—ป๐—ด

- Use a generic title (Data Engineer) as well as a role-specific title (Azure Data Engineer).
- Select all location types and tech hubs in India.
- Update your current location to Bangalore, Hyderabad, or Noida, as most companies hire from these locations.

๐Ÿฎ. ๐—ฆ๐—ธ๐—ถ๐—น๐—น ๐—˜๐—ป๐—ต๐—ฎ๐—ป๐—ฐ๐—ฒ๐—บ๐—ฒ๐—ป๐˜ ๐—ฎ๐—ป๐—ฑ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป

- Enhance in-demand skills through courses, certifications and projects to make your profile stand out to employers.

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๐Ÿฏ. ๐—๐—ผ๐—ถ๐—ป ๐—š๐—ฟ๐—ผ๐˜‚๐—ฝ๐˜€

- Jobs & Internship Opportunities: https://t.me/getjobss
- Data Analyst Jobs: https://t.me/jobs_SQL
- Web Development Jobs: https://t.me/webdeveloperjob
- Data Science Jobs: https://t.me/datasciencej
- Software Engineering Jobs: https://t.me/internshiptojobs
- Google Jobs: https://t.me/FAANGJob

๐Ÿฐ. ๐—ง๐—ฟ๐—ถ๐—ฐ๐—ธ๐˜€ ๐˜๐—ผ ๐—ด๐—ฒ๐˜ ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—–๐—ฎ๐—น๐—น๐˜€

- Visit the career portals of companies and apply to 10-15 recent openings.
- Cold email to companies/ HRs
- Apply for remote Jobs posted on telegram - https://t.me/jobs_us_uk

๐Ÿฑ. ๐—”๐˜€๐—ธ ๐—ณ๐—ผ๐—ฟ ๐—ฅ๐—ฒ๐—ณ๐—ฒ๐—ฟ๐—ฟ๐—ฎ๐—น๐˜€:

- When asking for a referral, ensure the person passes on your resume explicitly to the hiring manager.
- While asking for referral make sure to send Job id along with resume.

๐Ÿฒ. ๐˜„๐—ฒ๐—ฏ๐˜€๐—ถ๐˜๐—ฒ๐˜€ ๐˜๐—ผ ๐—บ๐—ฎ๐—ธ๐—ฒ ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ฟ๐—ฒ๐˜€๐˜‚๐—บ๐—ฒ ๐—ฏ๐—ฒ๐˜๐˜๐—ฒ๐—ฟ:

1. career.io
2. resume.io

๐—๐—ผ๐—ถ๐—ป ๐—บ๐˜† ๐—ฃ๐—ฒ๐—ฟ๐˜€๐—ผ๐—ป๐—ฎ๐—น ๐—–๐—ต๐—ฎ๐—ป๐—ป๐—ฒ๐—น๐˜€ -
- https://t.me/jobinterviewsprep
- https://t.me/InterviewBooks

If you've read so far, do LIKE and REPOST the post๐Ÿ‘
โค4
๐Ÿš€ ๐—ง๐—–๐—ฆ ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ โ€“ ๐—˜๐—ป๐—ฟ๐—ผ๐—น๐—น ๐—ก๐—ผ๐˜„!

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