๐๐ฟ๐ฒ๐๐ต๐ฒ๐ฟ๐ ๐ต๐ถ๐ฟ๐ถ๐ป๐ด ๐ณ๐ผ๐ฟ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐, ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐ฅ๐ฅ๐ฅ
https://www.linkedin.com/posts/mandarmpatil_interested-dataanalyst-datascience-activity-7214983924681216000-zmqn
https://www.linkedin.com/posts/mandarmpatil_interested-dataanalyst-datascience-activity-7214983924681216000-zmqn
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#interested #dataanalyst #datascience #recruitment #fresher #careerโฆ | Mandar Patil | 109 comments
Data Analyst hiring Freshers ๐ฅ
1. American Express hiring Analyst-Data Science
Exp: 0-3 Year
https://lnkd.in/drkeWvnV
2. Cognizant is hiring Business Analyst
Experience: Freshers/ Experienced
https://lnkd.in/dSHEvgCD
3. Data Science and Data Analyst: โฆ
1. American Express hiring Analyst-Data Science
Exp: 0-3 Year
https://lnkd.in/drkeWvnV
2. Cognizant is hiring Business Analyst
Experience: Freshers/ Experienced
https://lnkd.in/dSHEvgCD
3. Data Science and Data Analyst: โฆ
๐4๐ฅ2
Gartner is hiring Data Analysts to join their Data Modelling & Analytics team
Location: Gurgaon
Experience: 6 months to 2 years of experience.
Key Skills: Advanced excel, Python, SQL and Power BI.
You can go through the detailed JD and apply on the link:
https://gartner.wd5.myworkdayjobs.com/EXT/job/Gurgaon/Operations-Specialist--Advanced-excel--Python--SQL---Power-BI-required-_89996
https://www.linkedin.com/posts/pankhuri-mohan_operations-specialist-advanced-excel-python-activity-7214867669043269633-o9kq
Location: Gurgaon
Experience: 6 months to 2 years of experience.
Key Skills: Advanced excel, Python, SQL and Power BI.
You can go through the detailed JD and apply on the link:
https://gartner.wd5.myworkdayjobs.com/EXT/job/Gurgaon/Operations-Specialist--Advanced-excel--Python--SQL---Power-BI-required-_89996
https://www.linkedin.com/posts/pankhuri-mohan_operations-specialist-advanced-excel-python-activity-7214867669043269633-o9kq
๐1
Data Analyst hiring Freshers ๐ฅ
1. American Express Analyst-Data Science
Exp: 0-3 Year
https://www.linkedin.com/jobs/view/3962967350
2. Cognizant is hiring Business Analyst
Experience: Freshers/ Experienced
https://careers.cognizant.com/india-en/jobs/00058304611/business-analyst-payments-domain/
3. Genpact is hiring Associate, Data Analyst
Experienc๏ปฟe: Freshers/ Experienced
https://genpact.taleo.net/careersection/sgy_external_career_section/jobdetail.ftl?src=DS-10971&job=1357260
https://genpact.taleo.net/careersection/sgy_external_career_section/jobdetail.ftl?src=DS-10971&job=1383219
4. WM is hiring for Junior Analyst
https://emcm.fa.us2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/WMCareers/job/2320463
5. Mika Tech Data Scientist (Remote)
Exp: Fresher
https://internshala.com/job/details/fresher-remote-data-scientist-job-at-mika-tech1720071765
WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
Telegram Link: https://t.me/dataanalyticsbuddy
6. Sunflow Technology Data Analytics Executive (Remote)
Exp: 0-1 Year
https://internshala.com/job/details/fresher-remote-part-time-data-analytics-executive-job-at-sunflow-technology1720089674
7. Money Honey Financial Services Private Limited Business Analyst
Exp: 0-1 Year
https://internshala.com/job/details/fresher-business-analyst-job-in-mumbai-at-money-honey-financial-services-private-limited1719903843
8. Sunflow Technology Big Data Executive
Exp: 0-1 Year
https://internshala.com/job/details/fresher-remote-part-time-big-data-executive-job-at-sunflow-technology1719829655
9. Systemic Altruism AI Engineer (Remote)
Exp: Fresher
https://internshala.com/job/details/fresher-remote-ai-engineer-job-at-systemic-altruism1719982599
10. Nestlima Canada Data Scientist (Remote)
Exp: 0-4 Year
https://internshala.com/job/details/remote-data-scientist-job-at-nestlima-canada1719810697
11. Haptik Data Analyst / Data Scientist
Exp: Fresher
https://www.linkedin.com/jobs/view/3964358871
๐WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
๐Telegram Link: https://t.me/dataanalyticsbuddy
Like for more โค๏ธ
All the best ๐๐
1. American Express Analyst-Data Science
Exp: 0-3 Year
https://www.linkedin.com/jobs/view/3962967350
2. Cognizant is hiring Business Analyst
Experience: Freshers/ Experienced
https://careers.cognizant.com/india-en/jobs/00058304611/business-analyst-payments-domain/
3. Genpact is hiring Associate, Data Analyst
Experienc๏ปฟe: Freshers/ Experienced
https://genpact.taleo.net/careersection/sgy_external_career_section/jobdetail.ftl?src=DS-10971&job=1357260
https://genpact.taleo.net/careersection/sgy_external_career_section/jobdetail.ftl?src=DS-10971&job=1383219
4. WM is hiring for Junior Analyst
https://emcm.fa.us2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/WMCareers/job/2320463
5. Mika Tech Data Scientist (Remote)
Exp: Fresher
https://internshala.com/job/details/fresher-remote-data-scientist-job-at-mika-tech1720071765
WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
Telegram Link: https://t.me/dataanalyticsbuddy
6. Sunflow Technology Data Analytics Executive (Remote)
Exp: 0-1 Year
https://internshala.com/job/details/fresher-remote-part-time-data-analytics-executive-job-at-sunflow-technology1720089674
7. Money Honey Financial Services Private Limited Business Analyst
Exp: 0-1 Year
https://internshala.com/job/details/fresher-business-analyst-job-in-mumbai-at-money-honey-financial-services-private-limited1719903843
8. Sunflow Technology Big Data Executive
Exp: 0-1 Year
https://internshala.com/job/details/fresher-remote-part-time-big-data-executive-job-at-sunflow-technology1719829655
9. Systemic Altruism AI Engineer (Remote)
Exp: Fresher
https://internshala.com/job/details/fresher-remote-ai-engineer-job-at-systemic-altruism1719982599
10. Nestlima Canada Data Scientist (Remote)
Exp: 0-4 Year
https://internshala.com/job/details/remote-data-scientist-job-at-nestlima-canada1719810697
11. Haptik Data Analyst / Data Scientist
Exp: Fresher
https://www.linkedin.com/jobs/view/3964358871
๐WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
๐Telegram Link: https://t.me/dataanalyticsbuddy
Like for more โค๏ธ
All the best ๐๐
Linkedin
American Express hiring Analyst-Data Science in Gurugram, Haryana, India | LinkedIn
Posted 3:37:28 PM. You Lead the Way. Weโve Got Your Back.With the right backing, people and businesses have the powerโฆSee this and similar jobs on LinkedIn.
๐3
Hiring for: BI Developer-
Experience - 2-5 Years
Locations - Indore, Noida (WFO)
Primary Skill - Any BI Tool (Tableau, Qlik, Power BI) + SQL + TSQL + ETL
Immediate joiners only, please share resumes at "aditi.jain@intellicus.com
Experience - 2-5 Years
Locations - Indore, Noida (WFO)
Primary Skill - Any BI Tool (Tableau, Qlik, Power BI) + SQL + TSQL + ETL
Immediate joiners only, please share resumes at "aditi.jain@intellicus.com
๐ฅ2โค1
Shiprocket is seeking talented Data Scientists and Sr. Data Scientists to drive impactful insights and AI solutions.
Do you have a passion for solving complex problems and turning data into actionable strategies? This is your chance to join a dynamic, fast-growing company that is revolutionizing the commerce logistics industry.
๐ Location: Gurgaon (WFO)
๐ Role: Data Scientist (2-3 years), Sr. Data Scientist (3+ years)
๐ง Interested? Reach out to adit.mishra@shiprocket.com to apply and be a part of our innovative team!
Do you have a passion for solving complex problems and turning data into actionable strategies? This is your chance to join a dynamic, fast-growing company that is revolutionizing the commerce logistics industry.
๐ Location: Gurgaon (WFO)
๐ Role: Data Scientist (2-3 years), Sr. Data Scientist (3+ years)
๐ง Interested? Reach out to adit.mishra@shiprocket.com to apply and be a part of our innovative team!
โค3
Blinkit is hiring for Data Analyst
Expected Salary: 15-25 LPA
Apply here:
https://linkedin.com/jobs/view/3967861517/?alternateChannel=search
Expected Salary: 15-25 LPA
Apply here:
https://linkedin.com/jobs/view/3967861517/?alternateChannel=search
Linkedin
Blinkit hiring Data Analyst in Gurugram, Haryana, India | LinkedIn
Posted 8:05:47 AM. Position Overview: As a Data Analyst specializing in Inventory Management, you will be responsibleโฆSee this and similar jobs on LinkedIn.
โค2
Goldman Sachs Graduate Hiring Program 2024-25
Job Role: Graduate Trainee
Qualifications: Non-engineering Bachelorโs Degree
Salary: Up to 16 LPA (Expected)
Batch: 2024/ 2025/ 2026
Experience: Freshers
Location: Bengaluru; Hyderabad, India
๐Apply Now: https://www.goldmansachs.com/careers/students/programs/india/graduate-campus-hiring-program.html
๐WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
๐Telegram Link: https://t.me/dataanalyticsbuddy
Like for more โค๏ธ
All the best ๐๐
Job Role: Graduate Trainee
Qualifications: Non-engineering Bachelorโs Degree
Salary: Up to 16 LPA (Expected)
Batch: 2024/ 2025/ 2026
Experience: Freshers
Location: Bengaluru; Hyderabad, India
๐Apply Now: https://www.goldmansachs.com/careers/students/programs/india/graduate-campus-hiring-program.html
๐WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
๐Telegram Link: https://t.me/dataanalyticsbuddy
Like for more โค๏ธ
All the best ๐๐
โค2
๐ ๐ฎ๐ฐ๐ต๐ถ๐ป๐ฒ ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐ค๐๐ฒ๐๐๐ถ๐ผ๐ป๐ ๐๐ถ๐๐ต ๐๐ฟ๐ฒ๐ฒ ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐๐ฅ๐ฅ๐ฅ
https://www.linkedin.com/posts/mandarmpatil_machine-learning-interview-questions-activity-7215180165813792768-tYVJ
https://www.linkedin.com/posts/mandarmpatil_machine-learning-interview-questions-activity-7215180165813792768-tYVJ
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Practical Scenario-Based Machine Learning Interview Questions for Entry-Level Machine Learning Engineers | Mandar Patil postedโฆ
Practical Scenario-Based Machine Learning Interview Questions for Entry-Level Machine Learning Engineers
Preparing for a machine learning engineer role? These practical, scenario-based interview questions will help you demonstrate your real-world problemโฆ
Preparing for a machine learning engineer role? These practical, scenario-based interview questions will help you demonstrate your real-world problemโฆ
๐2
Machine Learning Interview Questions.pdf
1.9 MB
Machine Learning Interview Questions๐ฅ๐ฅ๐ฅ
React โค๏ธ if you want more content like this
React โค๏ธ if you want more content like this
โค3๐ฅ1
Machine Learning Interview Questions for Entry-Level Machine Learning Engineers
1. What is Machine Learning?
Explain the basic concept and types of machine learning (supervised, unsupervised, and reinforcement learning).
2. Difference between AI, Machine Learning, and Deep Learning?
Define each term and describe how they are related to each other.
3. What is Overfitting and Underfitting?
Describe the concepts and how to address them.
4. Explain the Bias-Variance Tradeoff.
Discuss the tradeoff and its significance in model performance.
5. What is Cross-Validation?
Explain different cross-validation techniques and their importance.
6. Describe the process of Feature Engineering.
Discuss techniques used to create and select features for a model.
7. What are Confusion Matrix and its components?
Define and explain precision, recall, F1 score, and accuracy.
8. Explain Regularization and its types.
Discuss L1 (Lasso) and L2 (Ridge) regularization.
9. What is Gradient Descent?
Describe the algorithm and its variants (batch, stochastic, mini-batch).
10. Difference between Classification and Regression?
Provide examples of each type of problem.
11. Explain Principal Component Analysis (PCA).
Discuss how PCA is used for dimensionality reduction.
12. What is a Support Vector Machine (SVM)?
Describe the algorithm and its applications.
13. Explain K-Nearest Neighbors (KNN).
Discuss how KNN works and its pros and cons.
14. Describe Decision Trees and Random Forests.
Explain the algorithms and how Random Forests improve performance.
15. What is a Neural Network?
Define the basic components (neurons, layers, activation functions).
16. Difference between Bagging and Boosting?
Describe each technique and their use cases.
17. Explain Hyperparameter Tuning.
Discuss methods such as grid search and random search.
18. What are Ensemble Methods?
Explain how ensemble methods like stacking and voting improve model performance.
19. What is a ROC Curve?
Describe how it is used to evaluate model performance.
20. Explain the concept of Clustering.
Discuss different clustering algorithms (K-means, hierarchical, DBSCAN).
21. What are Recommender Systems?
Explain the types and how they work.
22. How do you handle Missing Data?
Describe different strategies for dealing with missing values.
23. What is a Time Series Forecasting?
Explain how time series data is different and the techniques used for forecasting.
24. What are Autoencoders?
Describe their architecture and use cases.
25. Explain the term 'Feature Scaling'.
Discuss different methods of scaling features.
26. What is a Confusion Matrix?
Describe its importance in evaluating classification models.
27. Difference between Parametric and Non-Parametric Models?
Define each and provide examples.
28. What are ROC and AUC?
Explain how they are used to measure model performance.
29. Describe Transfer Learning.
Explain how pre-trained models are used in transfer learning.
30. What is an Outlier?
Discuss how to detect and handle outliers in a dataset.
1. What is Machine Learning?
Explain the basic concept and types of machine learning (supervised, unsupervised, and reinforcement learning).
2. Difference between AI, Machine Learning, and Deep Learning?
Define each term and describe how they are related to each other.
3. What is Overfitting and Underfitting?
Describe the concepts and how to address them.
4. Explain the Bias-Variance Tradeoff.
Discuss the tradeoff and its significance in model performance.
5. What is Cross-Validation?
Explain different cross-validation techniques and their importance.
6. Describe the process of Feature Engineering.
Discuss techniques used to create and select features for a model.
7. What are Confusion Matrix and its components?
Define and explain precision, recall, F1 score, and accuracy.
8. Explain Regularization and its types.
Discuss L1 (Lasso) and L2 (Ridge) regularization.
9. What is Gradient Descent?
Describe the algorithm and its variants (batch, stochastic, mini-batch).
10. Difference between Classification and Regression?
Provide examples of each type of problem.
11. Explain Principal Component Analysis (PCA).
Discuss how PCA is used for dimensionality reduction.
12. What is a Support Vector Machine (SVM)?
Describe the algorithm and its applications.
13. Explain K-Nearest Neighbors (KNN).
Discuss how KNN works and its pros and cons.
14. Describe Decision Trees and Random Forests.
Explain the algorithms and how Random Forests improve performance.
15. What is a Neural Network?
Define the basic components (neurons, layers, activation functions).
16. Difference between Bagging and Boosting?
Describe each technique and their use cases.
17. Explain Hyperparameter Tuning.
Discuss methods such as grid search and random search.
18. What are Ensemble Methods?
Explain how ensemble methods like stacking and voting improve model performance.
19. What is a ROC Curve?
Describe how it is used to evaluate model performance.
20. Explain the concept of Clustering.
Discuss different clustering algorithms (K-means, hierarchical, DBSCAN).
21. What are Recommender Systems?
Explain the types and how they work.
22. How do you handle Missing Data?
Describe different strategies for dealing with missing values.
23. What is a Time Series Forecasting?
Explain how time series data is different and the techniques used for forecasting.
24. What are Autoencoders?
Describe their architecture and use cases.
25. Explain the term 'Feature Scaling'.
Discuss different methods of scaling features.
26. What is a Confusion Matrix?
Describe its importance in evaluating classification models.
27. Difference between Parametric and Non-Parametric Models?
Define each and provide examples.
28. What are ROC and AUC?
Explain how they are used to measure model performance.
29. Describe Transfer Learning.
Explain how pre-trained models are used in transfer learning.
30. What is an Outlier?
Discuss how to detect and handle outliers in a dataset.
๐3โค2
Practical Scenario-Based Machine Learning Interview Questions for Entry-Level Machine Learning Engineers
1. Scenario: Customer Churn Prediction
How would you approach building a model to predict customer churn for a subscription-based service?
What features would you consider, and how would you handle imbalanced classes?
2. Scenario: Recommendation System
Describe how you would design a recommendation system for an e-commerce platform.
What algorithms might you use, and how would you evaluate the performance of your recommendation system?
3. Scenario: Fraud Detection
How would you build a model to detect fraudulent transactions in a financial dataset?
What techniques would you use to handle class imbalance and feature selection?
4. Scenario: Image Classification
Explain how you would create a model to classify images into different categories.
What pre-processing steps would you take, and how would you handle overfitting in your model?
5. Scenario: Sentiment Analysis
How would you build a sentiment analysis model for customer reviews?
Describe the process of text preprocessing and the choice of algorithms for this task.
6. Scenario: Predictive Maintenance
Discuss how you would develop a predictive maintenance model for industrial machinery.
What types of data would you collect, and how would you implement and evaluate your model?
7. Scenario: Time Series Forecasting
How would you approach forecasting sales data for the next quarter?
What models are suitable for time series forecasting, and how would you handle seasonality and trends?
8. Scenario: Anomaly Detection
Describe how you would build an anomaly detection system for network security.
What techniques would you use, and how would you evaluate the effectiveness of your system?
9. Scenario: Natural Language Processing
How would you build a chatbot that can handle customer service inquiries?
What NLP techniques would you use, and how would you ensure the chatbot understands and responds accurately?
10. Scenario: Feature Engineering
Given a dataset with various features, how would you approach feature engineering to improve model performance?
Provide examples of techniques you would use for feature creation and selection.
11. Scenario: Model Deployment
After training a machine learning model, how would you deploy it into a production environment?
What steps would you take to monitor and maintain the modelโs performance?
12. Scenario: Model Interpretability
How would you ensure that your machine learning model is interpretable and explainable to stakeholders?
Discuss techniques and tools you would use for model interpretability.
13. Scenario: Hyperparameter Tuning
Explain how you would perform hyperparameter tuning for a machine learning model.
What methods would you use, and how would you validate the results?
14. Scenario: Handling Missing Data
In a dataset with missing values, how would you handle the missing data before building a model?
Discuss different strategies and their impact on model performance.
15. Scenario: Model Evaluation
How would you evaluate the performance of a machine learning model in a real-world scenario?
Discuss different evaluation metrics and their relevance to specific problems.
1. Scenario: Customer Churn Prediction
How would you approach building a model to predict customer churn for a subscription-based service?
What features would you consider, and how would you handle imbalanced classes?
2. Scenario: Recommendation System
Describe how you would design a recommendation system for an e-commerce platform.
What algorithms might you use, and how would you evaluate the performance of your recommendation system?
3. Scenario: Fraud Detection
How would you build a model to detect fraudulent transactions in a financial dataset?
What techniques would you use to handle class imbalance and feature selection?
4. Scenario: Image Classification
Explain how you would create a model to classify images into different categories.
What pre-processing steps would you take, and how would you handle overfitting in your model?
5. Scenario: Sentiment Analysis
How would you build a sentiment analysis model for customer reviews?
Describe the process of text preprocessing and the choice of algorithms for this task.
6. Scenario: Predictive Maintenance
Discuss how you would develop a predictive maintenance model for industrial machinery.
What types of data would you collect, and how would you implement and evaluate your model?
7. Scenario: Time Series Forecasting
How would you approach forecasting sales data for the next quarter?
What models are suitable for time series forecasting, and how would you handle seasonality and trends?
8. Scenario: Anomaly Detection
Describe how you would build an anomaly detection system for network security.
What techniques would you use, and how would you evaluate the effectiveness of your system?
9. Scenario: Natural Language Processing
How would you build a chatbot that can handle customer service inquiries?
What NLP techniques would you use, and how would you ensure the chatbot understands and responds accurately?
10. Scenario: Feature Engineering
Given a dataset with various features, how would you approach feature engineering to improve model performance?
Provide examples of techniques you would use for feature creation and selection.
11. Scenario: Model Deployment
After training a machine learning model, how would you deploy it into a production environment?
What steps would you take to monitor and maintain the modelโs performance?
12. Scenario: Model Interpretability
How would you ensure that your machine learning model is interpretable and explainable to stakeholders?
Discuss techniques and tools you would use for model interpretability.
13. Scenario: Hyperparameter Tuning
Explain how you would perform hyperparameter tuning for a machine learning model.
What methods would you use, and how would you validate the results?
14. Scenario: Handling Missing Data
In a dataset with missing values, how would you handle the missing data before building a model?
Discuss different strategies and their impact on model performance.
15. Scenario: Model Evaluation
How would you evaluate the performance of a machine learning model in a real-world scenario?
Discuss different evaluation metrics and their relevance to specific problems.
๐4
Data Science and Data Analst Job Hiring Updates
Company: AKS ProTalent
Role: Data or Business Analyst
Exp: Fresher
Apply Now: https://lnkd.in/dh2fTVtp
Company: ConTecHub
Role: Data Analyst
Exp: Fresher
Apply Now: https://lnkd.in/dZyYHNKv
Company: Birdeye Australia
Role: Data Scientist
Exp: Fresher
Apply Now: https://lnkd.in/dsgrVRw2
Company: FieldAssist
Role: Data Analyst (PowerBI)
Exp: Fresher
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Company: Consulting And Beyond
Role: Junior Data Analyst
Exp: 0-1 yr
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Company: IDFC FIRST Bharat
Role: Data Analyst
Exp: 0-2 yrs
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Telegram Link: https://t.me/dataanalyticsbuddy
Company: AtliQ Technologies
Role: Data Scientist
Exp: 1-3 yrs
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Company: Black Piano
Role: Data Engineer
Exp: 1+ yrs
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Company: ProcDNA
Role: Data Engineer
Exp: 2+ yrs
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Company โ Ai Unika
Role โ Artificial Intelligence
Engineer Exp. โ 2 yr
Apply Here โ https://lnkd.in/d9xqQwkq
๐WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
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Like for more โค๏ธ
All the best ๐๐
Company: AKS ProTalent
Role: Data or Business Analyst
Exp: Fresher
Apply Now: https://lnkd.in/dh2fTVtp
Company: ConTecHub
Role: Data Analyst
Exp: Fresher
Apply Now: https://lnkd.in/dZyYHNKv
Company: Birdeye Australia
Role: Data Scientist
Exp: Fresher
Apply Now: https://lnkd.in/dsgrVRw2
Company: FieldAssist
Role: Data Analyst (PowerBI)
Exp: Fresher
Apply Now: https://lnkd.in/dY9ydz7N
WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
Company: Consulting And Beyond
Role: Junior Data Analyst
Exp: 0-1 yr
Apply Now: https://lnkd.in/d9BePWDc
Company: IDFC FIRST Bharat
Role: Data Analyst
Exp: 0-2 yrs
Apply Now: https://lnkd.in/dkSqAXcm
Telegram Link: https://t.me/dataanalyticsbuddy
Company: AtliQ Technologies
Role: Data Scientist
Exp: 1-3 yrs
Apply Now: https://lnkd.in/dp7f_2FT
Company: Black Piano
Role: Data Engineer
Exp: 1+ yrs
Apply Now: https://lnkd.in/dDJYwBWZ
Company: ProcDNA
Role: Data Engineer
Exp: 2+ yrs
Apply Now: https://lnkd.in/ddcrFztY
Company โ Ai Unika
Role โ Artificial Intelligence
Engineer Exp. โ 2 yr
Apply Here โ https://lnkd.in/d9xqQwkq
๐WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
๐Telegram Link: https://t.me/dataanalyticsbuddy
Like for more โค๏ธ
All the best ๐๐
๐ฅ2๐1
Hey hustlers, I hope you're doing great.
Welcome Day 2 of the ๐๐๐๐๐น๐ฒ๐ฟ๐๐น๐ฒ๐ฟ๐ ๐๐ผ ๐ฏ๐ฒ๐ฐ๐ผ๐บ๐ฒ ๐ฎ๐๐ฝ๐ถ๐ฟ๐ถ๐ป๐ด ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ ๐๐ผ ๐๐ผ๐ฟ๐ธ๐ถ๐ป๐ด ๐ฎ๐ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ challenge.
Today we have to learn the mathematics and statistics part, which is very essential because these two are used in Python, SQL, and Excel too, so we need to have a solid grip on these fundamentals of data analytics.
Here I'm sharing a few YouTube tutorials and resources so that you can go through them and complete today's challenge by the end of the day and don't forget to work on your health which is another essential part of this challenge
https://www.youtube.com/watch?v=o7WkGYIPUM8&list=PLunlGNVWDAaY7AeDDzTeu4-DD3g7zmAXs
W3School Statistics Tutorial:https://www.w3schools.com/statistics/
Looking forward to your responses.
Welcome Day 2 of the ๐๐๐๐๐น๐ฒ๐ฟ๐๐น๐ฒ๐ฟ๐ ๐๐ผ ๐ฏ๐ฒ๐ฐ๐ผ๐บ๐ฒ ๐ฎ๐๐ฝ๐ถ๐ฟ๐ถ๐ป๐ด ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ ๐๐ผ ๐๐ผ๐ฟ๐ธ๐ถ๐ป๐ด ๐ฎ๐ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ challenge.
Today we have to learn the mathematics and statistics part, which is very essential because these two are used in Python, SQL, and Excel too, so we need to have a solid grip on these fundamentals of data analytics.
Here I'm sharing a few YouTube tutorials and resources so that you can go through them and complete today's challenge by the end of the day and don't forget to work on your health which is another essential part of this challenge
https://www.youtube.com/watch?v=o7WkGYIPUM8&list=PLunlGNVWDAaY7AeDDzTeu4-DD3g7zmAXs
W3School Statistics Tutorial:https://www.w3schools.com/statistics/
Looking forward to your responses.
YouTube
Statistics For Data Analytics | Complete Syllabus | Data Science | Statistics Tutorial | Part 1
In this video, we present the complete syllabus for our "Statistics for Data Analytics" course. Whether you're a data enthusiast, student, or professional looking to sharpen your statistical skills, this syllabus overview will give you a sneak peek into whatโฆ
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PrepNPlaced pinned ยซHey hustlers, I hope you're doing great. Welcome Day 2 of the ๐๐๐๐๐น๐ฒ๐ฟ๐๐น๐ฒ๐ฟ๐ ๐๐ผ ๐ฏ๐ฒ๐ฐ๐ผ๐บ๐ฒ ๐ฎ๐๐ฝ๐ถ๐ฟ๐ถ๐ป๐ด ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ ๐๐ผ ๐๐ผ๐ฟ๐ธ๐ถ๐ป๐ด ๐ฎ๐ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ challenge. Today we have to learn the mathematics and statistics part, which is very essential because these two are usedโฆยป
Genpact is hiring!
Position: Management Trainee - Python Developer
Qualifications: Bachelor's degree
Salary: 5 - 8 LPA (Expected)
Experience: Entry Level
Location: Hyderabad/ Bangalore
๐Apply Now: https://genpact.taleo.net/careersection/sgy_external_career_section/jobdetail.ftl?src=DS-10971&job=1383932
https://genpact.taleo.net/careersection/sgy_external_career_section/jobdetail.ftl?src=DS-10971&job=1381781
Position: Management Trainee - Python Developer
Qualifications: Bachelor's degree
Salary: 5 - 8 LPA (Expected)
Experience: Entry Level
Location: Hyderabad/ Bangalore
๐Apply Now: https://genpact.taleo.net/careersection/sgy_external_career_section/jobdetail.ftl?src=DS-10971&job=1383932
https://genpact.taleo.net/careersection/sgy_external_career_section/jobdetail.ftl?src=DS-10971&job=1381781
โค1
Philips is hiring Data Analyst
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Job Title: Pricing Data Analyst - IGT-D (Hybrid, Colorado Springs)
Apply Link: https://philips.wd3.myworkdayjobs.com/jobs-and-careers/job/Colorado-Springs/Pricing-Data-Analyst---IGT-D--Hybrid--Colorado-Springs-_530318/
Oorwin is hiring for Python Developer
Experience: 1 - 3 Year(s)
Expected CTC: 8 - 12 Lpa
Apply here: https://unstop.com/jobs/python-developer-oorwin-labs-india-private-limited-1065619
Experience: 1 - 3 Year(s)
Expected CTC: 8 - 12 Lpa
Apply here: https://unstop.com/jobs/python-developer-oorwin-labs-india-private-limited-1065619
Unstop
Python Developer - Oorwin Labs India Private Limited - Hyderabad | 1065619 // Unstop
Become a Python Developer at Oorwin Labs India Private Limited and get the best salary in the industry. Click the link to apply now and advance your career. | 2024 | 1065619
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Broadridge is hiring for Full Stack Engineer (Python)
Expected Salary: 6-10 LPA
Apply here:
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Expected Salary: 6-10 LPA
Apply here:
https://broadridge.wd5.myworkdayjobs.com/Careers/job/Bengaluru-EPIP-Industrial-Area/Full-Stack-Engineer--Python-_JR1065254-1?trid=2d92f286-613b-4daf-9dfa-6340ffbecf73+
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Data Science Job Hiring
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Like for more โค๏ธ
All the best ๐๐
Company: Jivichem Synthesis Private Limited
Role: Machine Learning Internship
Exp: Fresher
Apply Now: https://lnkd.in/ds29dQuA
Company: Guruji Astro
Role: Data Analytics Internship
Exp: Fresher
Apply Now: https://lnkd.in/dgSiNyj5
Company: Super Scholar
Role: Junior Data Analyst
Exp: Fresher
Apply Now: https://lnkd.in/ddmGD5Ty
Company: SkillLabs
Role: Data Analyst
Exp: Fresher
Apply Now: https://lnkd.in/dA8DWsGR
Company: American Express
Role: Analyst-Data Analytics
Exp: Fresher
Apply Now: https://lnkd.in/dQmctNH6
Company: Pranathi Software Services Pvt. Ltd
Role: Business Analyst - Artificial Intelligence
Exp: 0-2 yrs
Apply Now: https://lnkd.in/dC-uixMG
WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
Company: Prodian
Role: Data Engineer/Analyst
Exp: 0-1 yrs
Apply Now: https://lnkd.in/dkiKM7bF
Company: NXP Semiconductors
Role: Data Scientist
Exp: 1 yr
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Telegram Link: https://t.me/dataanalyticsbuddy
Company: Astra Capital
Role: Data Engineer
Exp: 2+ yrs
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Company: Algoscale
Role: Data Engineer
Exp: 2 yr
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๐WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
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๐ช๐ต๐ ๐ผ๐๐ฒ๐ฟ๐ฐ๐ผ๐บ๐ถ๐ป๐ด ๐ผ๐๐ฟ ๐ณ๐ฒ๐ฎ๐ฟ๐ ๐ถ๐ ๐ต๐ฒ๐น๐ฝ๐ณ๐๐น ๐ณ๐ผ๐ฟ ๐ผ๐๐ฟ ๐ผ๐๐ป ๐ด๐ฟ๐ผ๐๐๐ต ๐ฎ๐ป๐ฑ ๐ฑ๐ฒ๐๐ฒ๐น๐ผ๐ฝ๐บ๐ฒ๐ป๐๐ฅ๐ฅ๐ฅ
https://www.linkedin.com/posts/mandarmpatil_fearlessliving-embracethejourney-yougotthis-activity-7215542589314220033-lLQh
https://www.linkedin.com/posts/mandarmpatil_fearlessliving-embracethejourney-yougotthis-activity-7215542589314220033-lLQh
Linkedin
Mandar Patil on LinkedIn: #fearlessliving #embracethejourney #yougotthis #overcomingfearโฆ | 77 comments
Are Your Fears Sabotaging Your Success? Here's How to Turn Them Around! ๐
We all dream of being fearless. Imagine yourself boldly pursuing your passionsโฆ | 77 comments on LinkedIn
We all dream of being fearless. Imagine yourself boldly pursuing your passionsโฆ | 77 comments on LinkedIn
โค2
Cognizant is hiring
Position: Junior Data Analyst
Experienc๏ปฟe: Freshers
Location: Mumbai; Kolkata; Pune, India (Hybrid)
https://careers.cognizant.com/global-en/jobs/00059475331/trainee-junior-data-analyst/?src=SNS-102?JB-11500 (MUMBAI)
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๐WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
๐Telegram Link: https://t.me/dataanalyticsbuddy
Like for more โค๏ธ
All the best ๐๐
Position: Junior Data Analyst
Experienc๏ปฟe: Freshers
Location: Mumbai; Kolkata; Pune, India (Hybrid)
https://careers.cognizant.com/global-en/jobs/00059475331/trainee-junior-data-analyst/?src=SNS-102?JB-11500 (MUMBAI)
https://careers.cognizant.com/global-en/jobs/00059570581/trainee-junior-data-analyst/?src=SNS-102?JB-11500 (KOLKATA)
https://careers.cognizant.com/global-en/jobs/00059444541/junior-data-analyst/?src=SNS-102?JB-11500 (PUNE)
๐WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
๐Telegram Link: https://t.me/dataanalyticsbuddy
Like for more โค๏ธ
All the best ๐๐
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