Richard Kadey

Data Scientist || Power Platform Developer

[Hriday Kadam @hridaykadam]

i'm begging you: stop applying on job boards. cold email founders instead. the exact play, with the data:

1. find 25 startups that raised a seed round 2 to 9 months ago. fresh money means hiring. under 2 months they're still scrambling. free sources: inc42 and entrackr funding trackers, wellfound's recently funded filter.

2. keep only the ones under 30 people. below 30, the founder still reads their own inbox.

3. pull 2 contacts per startup: the founder plus whoever runs the function you want. emailing more than one contact lifts replies 93%.

4. the email: 90 to 120 words. line 1 is about their raise or their product, not you. subject 36 to 50 characters (long subjects get 32.7% more replies). personalize the body (+32.7%). no resume attached. end with one question: 'what are you struggling to hire for right now?'

5. send wednesday morning, 9 to 11, their timezone. best day in the data.

6. follow up once on day 4. a single follow-up adds 65.8% more replies. once more on day 9, then stop forever.

7. the math: 25 startups x 2 contacts = 50 emails. average cold outreach converts 8.5%, that's 4 replies even done plainly. stack the multipliers and you're at 8 to 12 replies, 3 to 4 calls, 1 to 2 offers.

50 emails and one weekend to build the list. job boards put you in a queue. this puts you in a conversation.

[nana aba @thenanaaba]

Keep your goals away from small minded people.

[Prajwal Tomar @PrajwalTomar_]

How I Built Good Supplements for my client in 2 Weeks Using @lovable + @cursor_ai

Good Supplements is a platform for biohackers and wellness enthusiasts to discover, organize, and share supplement stacks.

Here’s how I built this entire MVP step by step.

[Richard Kadey @dev_kadey]

@jrdegbe 😂😂😂

[Avi Chawla @_avichawla]

95% of Jupyter Notebook users don't know these 5 AWESOME tricks:

[Baby Girl 🥰🥰 @Ozikroh0]

How to handle your woman talking to another guy

Even as a woman, I know these are awesome tips 👏👏

[CJ Zafir @cjzafir]

An Open Source AI model {Deepseek r1} launched 72 hours ago.

This Chinese AI model just broke the internet.

People are running r1 model on:
- self hosted servers
- mobile phones
- raspberry pi
- mac books

Here're all the cool experiments, you check:
🧵

[Richard Kadey @dev_kadey]

@akshay_pachaar I have resorted to using sunmarytools.

[Richard Kadey @dev_kadey]

After numerous calls and emails, all I get is "we'll escalate it." WES, your customer service is terrible. All I want now is a refund. My reference number is 6637383.
@WESAdvisor @WorldEdServices

[Richard Kadey @dev_kadey]

Dealing with WES has been a frustrating experience. My evaluation was completed on November 5th, but I still haven't received it.
@WorldEdServices @WESAdvisor

[Richard Kadey @dev_kadey]

I paid for premium delivery on November 26th, which was supposed to take 3-5 days yet again delivery has not been done.

[Daily Dose of Data Science @DailyDoseOfDS_]

10 great Python packages for Data Science not known to many:

[Richard Kadey @dev_kadey]

I just published How Machine Learning Can Mitigate Fraud in the Financial Industry https://t.co/7OFBIg7IEu

#DataScience #MachineLearning #Fraud #AI

[Matt Dancho (Business Science) @mdancho84]

90% of data scientists don't learn time series forecasting with Python in their data science programs.

Let's fix this. This is how:

[Santiago @svpino]

Here is the video where I built an AI assistant who sees and listens to me.

It's all Python. It's only a few lines of code. Video has step-by-step instructions on how to do the same.

Great example of what you could do with today's tech.

[Richard Kadey @dev_kadey]

@thenaijacarguy @datafrik_co This is great. I believe knowledge in statistics is also key.

[Akshay 🚀 @akshay_pachaar]

Object oriented programming in Python, clearly explained:

[Richard Kadey @dev_kadey]

@clcoding Answer is 2.

Reason: Even though the Apple class reference Fruit class the attributes of Fruit class are not inherited due to the absence of super()__init__() method.

[Santiago @svpino]

One skill for the top 1%:

Building real-time data pipelines and stream processing.

Everywhere I go, companies need to process data as fast as they produce it. It's hard to find people who know how to do this well, but companies are willing to pay exceptionally well for this.

Apache Kafka and Flink are the industry standards streaming platforms for high-performance data pipelines. Unfortunately, most streaming libraries are Java-based and offer a Python wrapper.

If you are a Python developer, here is an open-source alternative:

Quix Streams is a library that works with Kafka using pure Python. It's lightweight and has a beautiful and straightforward interface. Here's their GitHub repository:

https://t.co/Og1YvJGOQZ

You can use Quix to build stream processing pipelines in pure Python, including feature engineering, pre-computations, inference, and real-time machine learning.

The attached sample shows a simple aggregation and will give you a taste of what it’s like to build with Quix.

Thanks to the Quix team for collaborating with me on this post.

[Richard Kadey @dev_kadey]

CBG