Unsiloed AI is hiring for 10x ML Engineers to join our team full-time. Apply below and be part of a fast-moving team solving hard AI problems in document intelligence.
Experience: 1-3 years
CTC: 25-30 lpa (base)
https://app.dover.com/apply/Unsiloed-Ai/368c656d-764b-4eaf-87a7-ea22f665dc1a
Experience: 1-3 years
CTC: 25-30 lpa (base)
https://app.dover.com/apply/Unsiloed-Ai/368c656d-764b-4eaf-87a7-ea22f665dc1a
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Machine Learning Jobs Remote | Best Guide by Data Simplifier
https://datasimplifier.com/machine-learning-jobs-remote/
https://datasimplifier.com/machine-learning-jobs-remote/
Data Simplifier
Machine Learning Jobs Remote | Best Guide by Data Simplifier - Data Simplifier
Hey data scientists, machine learning engineers, and career changers eager to learn. This is your ultimate guide to understanding the exciting world of machine learning jobs. We'll cover everything from entry-level machine learning jobs to those in the USAโฆ
๐ฐ How to become a data scientist in 2025?
๐จ๐ปโ๐ป If you want to become a data science professional, follow this path! I've prepared a complete roadmap with the best free resources where you can learn the essential skills in this field.
๐ข Step 1: Strengthen your math and statistics!
โ๏ธ The foundation of learning data science is mathematics, linear algebra, statistics, and probability. Topics you should master:
โ Linear algebra: matrices, vectors, eigenvalues.
๐ Course: MIT 18.06 Linear Algebra
โ Calculus: derivative, integral, optimization.
๐ Course: MIT Single Variable Calculus
โ Statistics and probability: Bayes' theorem, hypothesis testing.
๐ Course: Statistics 110
โโโโโ
๐ข Step 2: Learn to code.
โ๏ธ Learn Python and become proficient in coding. The most important topics you need to master are:
โ Python: Pandas, NumPy, Matplotlib libraries
๐ Course: FreeCodeCamp Python Course
โ SQL language: Join commands, Window functions, query optimization.
๐ Course: Stanford SQL Course
โ Data structures and algorithms: arrays, linked lists, trees.
๐ Course: MIT Introduction to Algorithms
โโโโโ
๐ข Step 3: Clean and visualize data
โ๏ธ Learn how to process and clean data and then create an engaging story from it!
โ Data cleaning: Working with missing values โโand detecting outliers.
๐ Course: Data Cleaning
โ Data visualization: Matplotlib, Seaborn, Tableau
๐ Course: Data Visualization Tutorial
โโโโโ
๐ข Step 4: Learn Machine Learning
โ๏ธ It's time to enter the exciting world of machine learning! You should know these topics:
โ Supervised learning: regression, classification.
โ Unsupervised learning: clustering, PCA, anomaly detection.
โ Deep learning: neural networks, CNN, RNN
๐ Course: CS229: Machine Learning
โโโโโ
๐ข Step 5: Working with Big Data and Cloud Technologies
โ๏ธ If you're going to work in the real world, you need to know how to work with Big Data and cloud computing.
โ Big Data Tools: Hadoop, Spark, Dask
โ Cloud platforms: AWS, GCP, Azure
๐ Course: Data Engineering
โโโโโ
๐ข Step 6: Do real projects!
โ๏ธ Enough theory, it's time to get coding! Do real projects and build a strong portfolio.
โ Kaggle competitions: solving real-world challenges.
โ End-to-End projects: data collection, modeling, implementation.
โ GitHub: Publish your projects on GitHub.
๐ Platform: Kaggle๐ Platform: ods.ai
โโโโโ
๐ข Step 7: Learn MLOps and deploy models
โ๏ธ Machine learning is not just about building a model! You need to learn how to deploy and monitor a model.
โ MLOps training: model versioning, monitoring, model retraining.
โ Deployment models: Flask, FastAPI, Docker
๐ Course: Stanford MLOps Course
โโโโโ
๐ข Step 8: Stay up to date and network
โ๏ธ Data science is changing every day, so it is necessary to update yourself every day and stay in regular contact with experienced people and experts in this field.
โ Read scientific articles: arXiv, Google Scholar
โ Connect with the data community:
๐ Site: Papers with code
๐ Site: AI Research at Google
๐จ๐ปโ๐ป If you want to become a data science professional, follow this path! I've prepared a complete roadmap with the best free resources where you can learn the essential skills in this field.
๐ข Step 1: Strengthen your math and statistics!
โ๏ธ The foundation of learning data science is mathematics, linear algebra, statistics, and probability. Topics you should master:
โ Linear algebra: matrices, vectors, eigenvalues.
๐ Course: MIT 18.06 Linear Algebra
โ Calculus: derivative, integral, optimization.
๐ Course: MIT Single Variable Calculus
โ Statistics and probability: Bayes' theorem, hypothesis testing.
๐ Course: Statistics 110
โโโโโ
๐ข Step 2: Learn to code.
โ๏ธ Learn Python and become proficient in coding. The most important topics you need to master are:
โ Python: Pandas, NumPy, Matplotlib libraries
๐ Course: FreeCodeCamp Python Course
โ SQL language: Join commands, Window functions, query optimization.
๐ Course: Stanford SQL Course
โ Data structures and algorithms: arrays, linked lists, trees.
๐ Course: MIT Introduction to Algorithms
โโโโโ
๐ข Step 3: Clean and visualize data
โ๏ธ Learn how to process and clean data and then create an engaging story from it!
โ Data cleaning: Working with missing values โโand detecting outliers.
๐ Course: Data Cleaning
โ Data visualization: Matplotlib, Seaborn, Tableau
๐ Course: Data Visualization Tutorial
โโโโโ
๐ข Step 4: Learn Machine Learning
โ๏ธ It's time to enter the exciting world of machine learning! You should know these topics:
โ Supervised learning: regression, classification.
โ Unsupervised learning: clustering, PCA, anomaly detection.
โ Deep learning: neural networks, CNN, RNN
๐ Course: CS229: Machine Learning
โโโโโ
๐ข Step 5: Working with Big Data and Cloud Technologies
โ๏ธ If you're going to work in the real world, you need to know how to work with Big Data and cloud computing.
โ Big Data Tools: Hadoop, Spark, Dask
โ Cloud platforms: AWS, GCP, Azure
๐ Course: Data Engineering
โโโโโ
๐ข Step 6: Do real projects!
โ๏ธ Enough theory, it's time to get coding! Do real projects and build a strong portfolio.
โ Kaggle competitions: solving real-world challenges.
โ End-to-End projects: data collection, modeling, implementation.
โ GitHub: Publish your projects on GitHub.
๐ Platform: Kaggle๐ Platform: ods.ai
โโโโโ
๐ข Step 7: Learn MLOps and deploy models
โ๏ธ Machine learning is not just about building a model! You need to learn how to deploy and monitor a model.
โ MLOps training: model versioning, monitoring, model retraining.
โ Deployment models: Flask, FastAPI, Docker
๐ Course: Stanford MLOps Course
โโโโโ
๐ข Step 8: Stay up to date and network
โ๏ธ Data science is changing every day, so it is necessary to update yourself every day and stay in regular contact with experienced people and experts in this field.
โ Read scientific articles: arXiv, Google Scholar
โ Connect with the data community:
๐ Site: Papers with code
๐ Site: AI Research at Google
#ArtificialIntelligence #AI #MachineLearning #LargeLanguageModels #LLMs #DeepLearning #NLP #NaturalLanguageProcessing #AIResearch #TechBooks #AIApplications #DataScience #FutureOfAI #AIEducation #LearnAI #TechInnovation #AIethics #GPT #BERT #T5 #AIBook #data
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Anyscale Hiring !!
Role - ML Engineer
Exp - fresher
Link - https://www.linkedin.com/jobs/view/4157974677
Role - ML Engineer
Exp - fresher
Link - https://www.linkedin.com/jobs/view/4157974677
Linkedin
Anyscale hiring Software Engineer - Reinforcement Learning in Bengaluru, Karnataka, India | LinkedIn
Posted 1:14:14 AM. About Anyscale:At Anyscale, we're on a mission to democratize distributed computing and make itโฆSee this and similar jobs on LinkedIn.
Hi All, ๐๐ผ๐๐๐ผ๐ป ๐๐ผ๐ป๐๐๐น๐๐ถ๐ป๐ด ๐๐ฟ๐ผ๐๐ฝ (๐๐๐) is hiring Data Scientists and Senior Data Scientists for its tech build and design unit ๐๐๐ ๐ซ. Weโre looking for great talent to grow the team in India!
๐๐ญ๐ฆ๐ข๐ด๐ฆ ๐ฏ๐ฐ๐ต๐ฆ ๐ต๐ฉ๐ข๐ต ๐ต๐ฉ๐ฆ๐ด๐ฆ ๐ณ๐ฐ๐ญ๐ฆ๐ด ๐ณ๐ฆ๐ฒ๐ถ๐ช๐ณ๐ฆ ๐ต๐ณ๐ข๐ท๐ฆ๐ญ ๐ต๐ฐ ๐ค๐ญ๐ช๐ฆ๐ฏ๐ต ๐ญ๐ฐ๐ค๐ข๐ต๐ช๐ฐ๐ฏ๐ด, ๐ฎ๐ข๐ฏ๐ข๐จ๐ช๐ฏ๐จ ๐ฆ๐ฏ๐จ๐ข๐จ๐ฆ๐ฎ๐ฆ๐ฏ๐ต๐ด ๐ข๐ฏ๐ฅ ๐ค๐ญ๐ช๐ฆ๐ฏ๐ต ๐ณ๐ฆ๐ญ๐ข๐ต๐ช๐ฐ๐ฏ๐ด๐ฉ๐ช๐ฑ๐ด ๐ข๐ด ๐ธ๐ฆ๐ญ๐ญ.
More details can be found on this link: https://careers.bcg.com/global/en/job/52492
In case you are interested, feel free to send your resume directly to Singh.Kanishka@bcg.com with subject "Resume for DS/SDS role: <Name>".
๐๐ญ๐ฆ๐ข๐ด๐ฆ ๐ฏ๐ฐ๐ต๐ฆ ๐ต๐ฉ๐ข๐ต ๐ต๐ฉ๐ฆ๐ด๐ฆ ๐ณ๐ฐ๐ญ๐ฆ๐ด ๐ณ๐ฆ๐ฒ๐ถ๐ช๐ณ๐ฆ ๐ต๐ณ๐ข๐ท๐ฆ๐ญ ๐ต๐ฐ ๐ค๐ญ๐ช๐ฆ๐ฏ๐ต ๐ญ๐ฐ๐ค๐ข๐ต๐ช๐ฐ๐ฏ๐ด, ๐ฎ๐ข๐ฏ๐ข๐จ๐ช๐ฏ๐จ ๐ฆ๐ฏ๐จ๐ข๐จ๐ฆ๐ฎ๐ฆ๐ฏ๐ต๐ด ๐ข๐ฏ๐ฅ ๐ค๐ญ๐ช๐ฆ๐ฏ๐ต ๐ณ๐ฆ๐ญ๐ข๐ต๐ช๐ฐ๐ฏ๐ด๐ฉ๐ช๐ฑ๐ด ๐ข๐ด ๐ธ๐ฆ๐ญ๐ญ.
More details can be found on this link: https://careers.bcg.com/global/en/job/52492
In case you are interested, feel free to send your resume directly to Singh.Kanishka@bcg.com with subject "Resume for DS/SDS role: <Name>".
BCG
Data Scientist / Senior Data Scientist, India - BCG X in Mumbai, Maharashtra, India | Data Science and Analytics at BCG
Apply for Data Scientist / Senior Data Scientist, India - BCG X job with BCG in Mumbai, Maharashtra, India. Data Science and Analytics at BCG
Company Name : Spyne
Role : SDE 1 - Backend and Computer Vision Researcher
Batch : 2024/23/22
Link :
https://spyneai.keka.com/careers/jobdetails/45911
https://spyneai.keka.com/careers/jobdetails/53195
โ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธ
๐GigaML is hiring for Founding Full Stack Engineer
Salary: 60-100 LPA
Apply here: https://app.flexiple.com/job-description/10633
โ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธ
Role : SDE 1 - Backend and Computer Vision Researcher
Batch : 2024/23/22
Link :
https://spyneai.keka.com/careers/jobdetails/45911
https://spyneai.keka.com/careers/jobdetails/53195
โ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธ
๐GigaML is hiring for Founding Full Stack Engineer
Salary: 60-100 LPA
Apply here: https://app.flexiple.com/job-description/10633
โ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธ
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Hiring a highly skilled Data Scientist with strong expertise in Develops predictive models using Machine Learning algorithms, Random Forest, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, good knowledge in Python for a prestigious client based in Bangalore. The ideal candidates should possess strong academic backgrounds from Tier 1 and Tier 2 colleges.
Experience: 3.5 to 6 Years
Location: Bangalore
Notice Period: Immediate to 30 Days
If youโre interested or you have a strong network of professionals who fits this profile, please share their resumes to shruthik@novotreeminds.com
Experience: 3.5 to 6 Years
Location: Bangalore
Notice Period: Immediate to 30 Days
If youโre interested or you have a strong network of professionals who fits this profile, please share their resumes to shruthik@novotreeminds.com
Forwarded from Data Analyst Jobs
MICROSOFT is Hiring for DATA AND APPLIED SCIENTIST II
Apply Now:- https://jobs.careers.microsoft.com/us/en/job/1810546/Data-and-Applied-Scientist-II?jobsource=linkedin
๐WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
๐Telegram Link: https://t.me/addlist/4q2PYC0pH_VjZDk5
Like for more โค๏ธ
Apply Now:- https://jobs.careers.microsoft.com/us/en/job/1810546/Data-and-Applied-Scientist-II?jobsource=linkedin
๐WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
๐Telegram Link: https://t.me/addlist/4q2PYC0pH_VjZDk5
Like for more โค๏ธ
โค1๐1
Forwarded from Data Analyst Jobs
๐Deloitte is hiring for Data Science Intern
Experience: 0 - 1 year's
Expected Stipend: 3-5 LPA
Apply here: https://southasiacareers.deloitte.com/job/Bengaluru-Intern-Data-Science-Bengaluru-Digital-Excellence-Centre/36247044/
๐WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
๐Telegram Link: https://t.me/addlist/4q2PYC0pH_VjZDk5
Like for more โค๏ธ
Experience: 0 - 1 year's
Expected Stipend: 3-5 LPA
Apply here: https://southasiacareers.deloitte.com/job/Bengaluru-Intern-Data-Science-Bengaluru-Digital-Excellence-Centre/36247044/
๐WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
๐Telegram Link: https://t.me/addlist/4q2PYC0pH_VjZDk5
Like for more โค๏ธ
๐2โค1
Harman Hiring !!
Role - ML sde
Exp - fresher
Link - https://jobsearch.harman.com/careers/searchjobs/R-42351-2025
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Role - ML sde
Exp - fresher
Link - https://jobsearch.harman.com/careers/searchjobs/R-42351-2025
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big-book-of-data-engineering-2nd-edition-final.pdf
8.8 MB
The Big Book of Data Engineering
Databricks, 2nd ed, 2023
Databricks, 2nd ed, 2023
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