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Изходен канал @clockstackwheels · Post #1075 · 20.02

Айтишный опыт очень нелинейно конвертируется в деньги. Если у вас 3-5 лет опыта, и вы занимались развитием своих навыков, то можете получать зарплату мидла, пусть это будет X денег. За 10 лет опыта при продолжающемся развитии вы становитесь сеньором (кто-то быстрее, кто-то дольше), и тогда вы получаете 1.5X денег, ну может 1.75X, при очень большом везении 2X денег. Но если у вас 15-20 лет опыта, вам 2X+ никто не даст, и уж тем более 2.5-3X. Бывают отдельные случаи, когда какой-нибудь Бобук с офигенно раскрученным личным брендом получает миллионы (и то, на порнухе и казино), но глобально ситуация по рынку понятная. Получается, что после 10 лет опыта вы уже как бы достигли своей финансовой вершины в айти. Можно сместиться в руководство, но, во-первых, не каждому хочется, а, во-вторых, это требует иных навыков, которые тоже не у каждого есть. Да и не будет руководящих должностей на всех. А как там с другими профессиями? У некоторых профессий есть категории, разряды или формальные уровни квалификации, которые влияют на зарплату. Если вы сварщик шестого разряда или учитель высшей категории, то один этот факт будет добавлять к зарплате некоторый процент. Очень понятный путь прокачки. Но всё равно, когда упёрся в левел-кап, дальше уже роста не будет. А есть ли за что платить? Будет ли строитель с 20-летним опытом сильно больше уметь, чем строитель с 10-летним? Интуитивно кажется, что да, потому что 10 лет это типа 3-4 больших объекта, довольно мало. Уж точно 6-8 больших объектов звучат сильно солиднее. Видимо, зависит всё-таки от формата и сложности работы. У врачей, кажется, вообще никогда нельзя упереться в предел опыта. И по ощущениям тоже врач с 20 годами должен получать больше, чем с 10 (если в комментах есть врачи, расскажите, так ли это). Но в айти престарелые (по меркам айти) сеньоры сидят и тухнут. Я так BG3 бросил в середине третьего акта, потому что прокачка остановилась. К счастью, опыт в работе у меня складывался более интересный: сначала я пять лет пилил свои проекты с разной степенью успеха, потом пять лет был фрилансером, а теперь вот пять лет в энтерпрайзе. Точно есть, куда расти, и по навыкам и по деньгам. Существует ли ещё какая-то форма занятости? Свой айтишный бизнес, пожалуй, но тут уж совсем особые умения нужны. #life

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Repositorio data science

@repo_science · Post #3999 · 22.01.2024 г., 11:01

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Daily Channels

@dailychannels · Post #6767 · 23.03.2026 г., 01:00

Channel: Propheta Indicator Signals Members: ~2.5K 💢 Username: @propheta_indicator Description: 😎 WE MILK THE EXCHANGES! 🔥 Reviews & Results - @propheta_reviews 📊 Performance Reports - @propheta_reports 🤖 Get Access - @ProphetaAccountBot Contact us: @propheta_help 🏷 Tags: #crypto_fx_trading #crypto#trading#signals#analysis#news https://lve.to/4rck4ca4c6

Venezuelanalysis

@venanalysis · Post #1850 · 11.01.2025 г., 21:16

The Venezuelanalysis staff gathered to discuss the recent events surrounding Maduro’s third presidential term inauguration and the challenges ahead. The topics included an update on the situation on the ground, María Corina Machado's (fake?) arrest and the US response. Click to watch: https://venezuelanalysis.com/video/venezuelas-maduro-presidential-inauguration-recap-and-lookahead/ #Livestream#Analysis#Venezuela#PresidentialInauguration

Daily Channels

@dailychannels · Post #5943 · 26.03.2025 г., 13:00

Channel: Bitcoin Trading Nicole Members: ~20.77K 💢 Username: @bitcointradingnicole Description: Nicole Bitcoin Trading is a place to be, where experts calls are backedup with sound Technical analysis. t.me/PayoutProof t.me/BitcoinAlgoPumps t.me/CryptoTradingNicole For VIP & Pump Contact: @NicoleCrypto 🏷 Tags: #crypto_fx_trading #bitcoin#trading#crypto#analysis#investing https://telegramchannels.me/channels/bitcointradingnicole

Daily Channels

@dailychannels · Post #6000 · 11.04.2025 г., 01:00

Channel: Crypto Trading Signals ✅ Members: ~8.19K 💢 Username: @binancefuturetrading Description: Who are we? We are a group of professional traders who focus mainly on crypto publicity projects and crypto Trading. 🏷 Tags: #crypto_fx_trading #cryptocurrency#bitcoin#trading#analysis#investments https://telegramchannels.me/channels/binancefuturetrading

djangoproject

@djangoproject · Post #336 · 09.05.2017 г., 05:24

https://dzone.com/articles/pyflakes-passive-checker There are several code #analysis tools for Python. The most well known is pylint. Then there’s pychecker and now we’re moving on to #pyflakes. The pyflakes project is a part of something known as the Divmod Project. Pyflakes doesn’t actually execute the code it checks, unlike #pychecker. Of course, #pylint also doesn’t execute the code. Regardless, we’ll take a quick look at it and see how pyflakes works and if it’s better than the competition.

Crypto M - Crypto News

@CryptoM · Post #64526 · 09.04.2026 г., 06:14

🚀 Polymarket Traders' Earnings: Only 0.015% Achieve $5,000 Monthly Crypto analyst Andrey Sergeenkov's recent analysis reveals that a mere 0.015% of Polymarket traders managed to earn at least $5,000 monthly for four consecutive months. According to NS3.AI, the study examined trading data spanning from April 2024 to April 1, 2026, highlighting the challenges faced by traders in achieving consistent profitability on the platform. #Polymarket#Crypto#Trading#Earnings#Profitability#Analysis#NS3AI

Data Analytics

@sqlspecialist · Post #1644 · 23.05.2025 г., 18:46

✨The STAR method is a powerful technique used to answer behavioral interview questions effectively. It helps structure responses by focusing on Situation, Task, Action, and Result. For analytics professionals, using the STAR method ensures that you demonstrate your problem-solving abilities, technical skills, and business acumen in a clear and concise way. Here’s how the STAR method works, tailored for an analytics interview: 📍 1. Situation Describe the context or challenge you faced. For analysts, this might be related to data challenges, business processes, or system inefficiencies. Be specific about the setting, whether it was a project, a recurring task, or a special initiative. Example: “At my previous role as a data analyst at XYZ Company, we were experiencing a high churn rate among our subscription customers. This was a critical issue because it directly impacted revenue.”* 📍 2. Task Explain the responsibilities you had or the goals you needed to achieve in that situation. In analytics, this usually revolves around diagnosing the problem, designing experiments, or conducting data analysis. Example: “I was tasked with identifying the factors contributing to customer churn and providing actionable insights to the marketing team to help them improve retention.”* 📍 3. Action Detail the specific actions you took to address the problem. Be sure to mention any tools, software, or methodologies you used (e.g., SQL, Python, data #visualization tools, #statistical#models). This is your opportunity to showcase your technical expertise and approach to problem-solving. Example: “I collected and analyzed customer data using #SQL to extract key trends. I then used #Python for data cleaning and statistical analysis, focusing on engagement metrics, product usage patterns, and customer feedback. I also collaborated with the marketing and product teams to understand business priorities.”* 📍 4. Result Highlight the outcome of your actions, especially any measurable impact. Quantify your results if possible, as this demonstrates your effectiveness as an analyst. Show how your analysis directly influenced business decisions or outcomes. Example: “As a result of my analysis, we discovered that customers were disengaging due to a lack of certain product features. My insights led to a targeted marketing campaign and product improvements, reducing churn by 15% over the next quarter.”* Example STAR Answer for an Analytics Interview Question: Question: *"Tell me about a time you used data to solve a business problem."* Answer (STAR format): 🔻*S*: “At my previous company, our sales team was struggling with inconsistent performance, and management wasn’t sure which factors were driving the variance.” 🔻*T*: “I was assigned the task of conducting a detailed analysis to identify key drivers of sales performance and propose data-driven recommendations.” 🔻*A*: “I began by collecting sales data over the past year and segmented it by region, product line, and sales representative. I then used Python for #statistical#analysis and developed a regression model to determine the key factors influencing sales outcomes. I also visualized the data using #Tableau to present the findings to non-technical stakeholders.” 🔻*R*: “The analysis revealed that product mix and regional seasonality were significant contributors to the variability. Based on my findings, the company adjusted their sales strategy, leading to a 20% increase in sales efficiency in the next quarter.” Hope this helps you 😊

Repositorio data science

@repo_science · Post #3078 · 18.04.2023 г., 15:54

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