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#83 - The Truth About Freelancing in Data Science (And How to Succeed) | Jeremy Arancio cover
#83 - The Truth About Freelancing in Data Science (And How to Succeed) | Jeremy Arancio cover
Let's Talk AI

#83 - The Truth About Freelancing in Data Science (And How to Succeed) | Jeremy Arancio

#83 - The Truth About Freelancing in Data Science (And How to Succeed) | Jeremy Arancio

1h16 |27/08/2025
Play
undefined cover
undefined cover
#83 - The Truth About Freelancing in Data Science (And How to Succeed) | Jeremy Arancio cover
#83 - The Truth About Freelancing in Data Science (And How to Succeed) | Jeremy Arancio cover
Let's Talk AI

#83 - The Truth About Freelancing in Data Science (And How to Succeed) | Jeremy Arancio

#83 - The Truth About Freelancing in Data Science (And How to Succeed) | Jeremy Arancio

1h16 |27/08/2025
Play

Description

Data science freelancing is a test of both technical skill and strategic adaptability. 


In our conversation with Jérémy Arancio, we dissect the frameworks he uses to thrive: relentless upskilling, leveraging platforms like LinkedIn for visibility, and distinguishing between hype and practical tools in AI. 


From the nuanced differences of GenAI vs. NLP to the tactical mindset shift freelancing requires, this episode breaks down what separates sustainable data science careers from those that fizzle out.


Top Insights:

  • Freelancing is a means to learn and grow.

  • You will never feel fully prepared to start freelancing.

  • The journey of freelancing can be both rewarding and challenging.

  • AI should be used to solve specific business problems.

  • Content creation can help build connections and opportunities.

  • Choosing the right vehicle for your career is crucial.

  • Growth often comes from discomfort and challenges.

  • Networking on platforms like LinkedIn is valuable for career advancement.

  • Understanding the difference between Gen.AI and NLP is important.

  • Continuous learning is essential in the fast-paced tech industry.


Connect with Jeremy Arancio

Connect with Thomas Bustos


Hosted by Ausha. See ausha.co/privacy-policy for more information.

Description

Data science freelancing is a test of both technical skill and strategic adaptability. 


In our conversation with Jérémy Arancio, we dissect the frameworks he uses to thrive: relentless upskilling, leveraging platforms like LinkedIn for visibility, and distinguishing between hype and practical tools in AI. 


From the nuanced differences of GenAI vs. NLP to the tactical mindset shift freelancing requires, this episode breaks down what separates sustainable data science careers from those that fizzle out.


Top Insights:

  • Freelancing is a means to learn and grow.

  • You will never feel fully prepared to start freelancing.

  • The journey of freelancing can be both rewarding and challenging.

  • AI should be used to solve specific business problems.

  • Content creation can help build connections and opportunities.

  • Choosing the right vehicle for your career is crucial.

  • Growth often comes from discomfort and challenges.

  • Networking on platforms like LinkedIn is valuable for career advancement.

  • Understanding the difference between Gen.AI and NLP is important.

  • Continuous learning is essential in the fast-paced tech industry.


Connect with Jeremy Arancio

Connect with Thomas Bustos


Hosted by Ausha. See ausha.co/privacy-policy for more information.

Share

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Description

Data science freelancing is a test of both technical skill and strategic adaptability. 


In our conversation with Jérémy Arancio, we dissect the frameworks he uses to thrive: relentless upskilling, leveraging platforms like LinkedIn for visibility, and distinguishing between hype and practical tools in AI. 


From the nuanced differences of GenAI vs. NLP to the tactical mindset shift freelancing requires, this episode breaks down what separates sustainable data science careers from those that fizzle out.


Top Insights:

  • Freelancing is a means to learn and grow.

  • You will never feel fully prepared to start freelancing.

  • The journey of freelancing can be both rewarding and challenging.

  • AI should be used to solve specific business problems.

  • Content creation can help build connections and opportunities.

  • Choosing the right vehicle for your career is crucial.

  • Growth often comes from discomfort and challenges.

  • Networking on platforms like LinkedIn is valuable for career advancement.

  • Understanding the difference between Gen.AI and NLP is important.

  • Continuous learning is essential in the fast-paced tech industry.


Connect with Jeremy Arancio

Connect with Thomas Bustos


Hosted by Ausha. See ausha.co/privacy-policy for more information.

Description

Data science freelancing is a test of both technical skill and strategic adaptability. 


In our conversation with Jérémy Arancio, we dissect the frameworks he uses to thrive: relentless upskilling, leveraging platforms like LinkedIn for visibility, and distinguishing between hype and practical tools in AI. 


From the nuanced differences of GenAI vs. NLP to the tactical mindset shift freelancing requires, this episode breaks down what separates sustainable data science careers from those that fizzle out.


Top Insights:

  • Freelancing is a means to learn and grow.

  • You will never feel fully prepared to start freelancing.

  • The journey of freelancing can be both rewarding and challenging.

  • AI should be used to solve specific business problems.

  • Content creation can help build connections and opportunities.

  • Choosing the right vehicle for your career is crucial.

  • Growth often comes from discomfort and challenges.

  • Networking on platforms like LinkedIn is valuable for career advancement.

  • Understanding the difference between Gen.AI and NLP is important.

  • Continuous learning is essential in the fast-paced tech industry.


Connect with Jeremy Arancio

Connect with Thomas Bustos


Hosted by Ausha. See ausha.co/privacy-policy for more information.

Share

Embed

You may also like