Pyhton уже обязательный в требования к банковсим вакансиям согласно этой статье https://news.efinancialcareers.com/uk-en/3001136/python-for-banking-jobs
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Amazon The 2 and 5 Promise - это обещание кандидату дать фибдек после собеседование через 2 дня после телефонного собеседования и 5 дней после onsite собеседования. Кстати в Европе есть много вакансий в Амазон и некоторые из них имею возможность Sponsorship, но я не знаю как это работает. Есть крупный офис в Мюнхене, недавно открылся офис в Мадриде, AWS и Kindle в Люксембурге
Snowflake и Tableau это очень модно! А если еще и Slalom Consulting это внедрит, то вообще будет шоколадно) НО очень дорого!!!А вы что хотели. https://medium.com/slalom-data-analytics/unleash-an-avalanche-of-insights-with-snowflake-and-tableau-b9276a9d9191
Medium
Unleash an Avalanche of Insights with Snowflake and Tableau
Modern Data Architecture the Slalom way
Customer Analytics is the more versatile applications on data science across every industry.
Reading list by Steve Nouri
1-Customer Life Cycle:
https://lnkd.in/gEgBNJu
2-Recommend the Best Channels for Contact:
https://lnkd.in/gvJXmp5
3-Customer Lifetime Value:
https://lnkd.in/gpYnZX3
4-Clustering and Predictive Analysis of group problems:
https://lnkd.in/gchcPCA
5-Use Algorithms to Recommend Items to Customers in Python( Cross-selling, Up-selling ):
https://lnkd.in/gzzuFJh
Sample Dataset: https://lnkd.in/g9wZcmj
For Other Business Applications you can see at
1. Data Science Process https://lnkd.in/fMHtxYP
2. Data Visualization in Business https://lnkd.in/fYUCzgC
3. Understand How to answer Why https://lnkd.in/f396Dqg
4. Know ML Key Terminology https://lnkd.in/fCihY9W
5. Understand ML Implementation https://lnkd.in/f5aUbBM
6. ML Applications on Marketing https://lnkd.in/fUDGAQW
and Retail https://lnkd.in/fihPTJf
Reading list by Steve Nouri
1-Customer Life Cycle:
https://lnkd.in/gEgBNJu
2-Recommend the Best Channels for Contact:
https://lnkd.in/gvJXmp5
3-Customer Lifetime Value:
https://lnkd.in/gpYnZX3
4-Clustering and Predictive Analysis of group problems:
https://lnkd.in/gchcPCA
5-Use Algorithms to Recommend Items to Customers in Python( Cross-selling, Up-selling ):
https://lnkd.in/gzzuFJh
Sample Dataset: https://lnkd.in/g9wZcmj
For Other Business Applications you can see at
1. Data Science Process https://lnkd.in/fMHtxYP
2. Data Visualization in Business https://lnkd.in/fYUCzgC
3. Understand How to answer Why https://lnkd.in/f396Dqg
4. Know ML Key Terminology https://lnkd.in/fCihY9W
5. Understand ML Implementation https://lnkd.in/f5aUbBM
6. ML Applications on Marketing https://lnkd.in/fUDGAQW
and Retail https://lnkd.in/fihPTJf