The Data Scientist Show

By Daliana Liu

Listen to a podcast, please open Podcast Republic app. Available on Google Play Store.

Category: Technology

Open in Apple Podcasts

Open RSS feed

Open Website

Rate for this podcast

Subscribers: 2
Reviews: 0


Data science practitioners, AI researchers, and CTOs of AI companies share their career journeys and cools things they are working on. Hosted by Daliana Liu, senior data scientist. Available on all platforms. Apple: | Spotify: | YouTube: Follow Daliana for more data science and career tips Linkedin: Twitter:

Episode Date
Build successful end-to-end machine learning systems, ML engineers day-to-day and stakeholder management with Eugene Yan - The Data Scientist Show#015

Eugene Yan is a machine learning engineer at Amazon. He designs, builds, and operates machine learning systems that serve customers at scale. In his free time, he writes and speaks about data science on with 2,000+ subscribers.

We talked about how to build an end-to-end ML project successfully, machine learning best practices, his approach to tackle challenging problems, high-impact projects he worked on, how to communicate effectively with stakeholders, why writing documents is important, and how to get to the next level.

Subscribe to the channel and leave a comment if you enjoy the show!

You can follow Eugene on Twitter @eugeneyan

Dec 02, 2021
From data engineer to data scientist at Google, transition into DS from non-tech degree, salary negotiation, how to manage up with Sundas Khalid - The Data Scientist Show #014

Sundas Khalid is a senior analytics lead at Google. She started her career as a data engineer and transitioned into data science through self-learning. I met Sundas when we worked together at Amazon. She helped women of color negotiate a $1.4M in incremental salaries. She talks about careers in data science, personal finance, and salary negotiation on YouTube and Instagram.  

• We talked about how she transitioned from data engineer to data scientist 

• Data engineer vs data scientist pros and cons 

• How to grow to a senior data scientist 

• How to build a data science tool that has impact for the business

• 3 mistakes people make when negotiating salary  

• How to build wealth using your salary  

Her website:

Nov 25, 2021
Develop product sense to uplevel your data science career, how to influence product managers with data, crack product sense interview questions with Peter Knudson - The Data Scientist Show #013

Peter Knudson is a product manager of 10 years who focuses on innovative new experiences that help drive engagement in the ever evolving landscape of mobile and console games. He is also the author of the Amazon best selling book “Product Sense.”

We talk about what is product sense, how do data scientist develop product sense, what are product manager’s frustration when working with data scientists, how can data scientists influence product managers better, misconceptions about product management, common mistakes in product management.

Peter’s best selling book “Product Sense”:



Nov 17, 2021
The secret to improve mental health, future of data engineering, work life balance with Zach Wilson - The Data Scientist Show #012

Zach Wilson is a tech lead at Airbnb building data pipelines, previously he worked at Netflix and Facebook. Zach graduated from college at the age of 20 with degrees of math and computer science. He has over 80k followers on Linkedin.  

We talked about mental health, terminal level, promotions, work life balance, building audience on Linkedin, and the future of data engineering.  

For data engineering best practices, Zach's career journey, working in FAANG, please go to previous episode "Demystify data engineering" 

Zach's YouTube:

Nov 09, 2021
Demystify data engineering, 3 common mistakes, FAANG's culture, how to say no at work with Zach Wilson - The Data Scientist Show #011

Zach Wilson is a tech lead at Airbnb building data pipelines, previously he worked at Netflix and Facebook. Zach graduated from college at the age of 20 with degrees of math and computer science. He has over 80k followers on Linkedin.

We talked about common data engineering mistakes, best practices, softskills, how to say no at work, work experience in Facebook, Netflix, and Airbnb. This is part one of our conversation, and please go to next week’s episode for part two.

Zach's Linkedin:

Nov 04, 2021
Build a killer analytics dashboard for your CEO; data visualization best practices with Kate Strachnyi - The Data Scientist Show #010

Kate Strachnyi is the founder of DATAcated – delivering training on data visualization, data storytelling, and dashboard best practices. She has over 150k followers on Linkedin. We talked about how she got into data analytics without a background in math, what makes a good dashboard, how to work with executives, how to tell stories with data, what she’s looking for when hiring a data analyst, and the psychology of color!


Oct 28, 2021
Ace the data science interview; build kick-ass portfolio projects with Nick Singh - The Data Scientist Show #009

Nick Singh is a career coach and the co-author of "ace the data science interview". He has over 60k followers on Linkedin, and previously worked at Facebook and Google. We talked about how to prepare for data science interviews, how to build a portfolio, what makes a candidate stand out, how to write cold emails to recruiters, and his career journey. 

You can find his book on Amazon:

Nick's Linkedin:

Oct 21, 2021
Solving the brain with machine learning; the secret to a successful career with Konrad Kording - The Data Scientist Show #008

Konrad Kording is a neuroscientist and professor at the University of Pennsylvania. Konrad is trying to understand how the world and the brain works using data. He is known for his research in computational neuroscience. We talked about:

- Is evolution gradient descent?

- What makes a data scientist competitive?

- His three principles of doing good science

- Why do we need casual inference in AI?

- Should we optimize our brain's 'loss function' to make us happier?

- The secret to a good career

- Three rules he follows for doing good science

- Is deep learning a bubble?

- How did he get to where he's at today

Konrad's twitter:

The online community of computational neuroscientists he's working on:

Oct 14, 2021
How do data scientists get into blockchain? How to build a career by networking online, Greg Osuri - The Data Scientist Show #007

A seasoned open-source developer of 25+ years, Greg Osuri is the CEO and co-Founder of Akash Network, an open-source decentralized cloud that provides a fast, efficient, and low-cost application deployment.   

Prior to Akash Network, Greg founded AngelHack, the world’s largest hackathon organization with over 200,000 developers across 164 cities across the globe. At AngelHack, he helped launch several developer companies including Firebase, which was acquired by Google in 2014.   Greg launched his career at IBM and later designed Kaiser Permanente’s first cloud architecture. As an expert in open-source, distributed systems, and blockchain development, and an applied economist, Greg is a featured international speaker and has spoken recently at events including Kong Summit, Block-Con, and Block to the Future.   His work has been featured in top-tier publications including BeInCrypto, CoinDesk, Cointelegraph, Forbes, TechCrunch, and Yahoo! Finance. Greg was instrumental in the passing of California’s first Blockchain law, providing the first expert-witness testimony at the Senate.  

About Akash Network: Akash Network, the world's first decentralized and open-source cloud, accelerates deployment, scale, efficiency and price performance for high-growth industries like blockchain and machine learning/AI.   

Greg's Twitter:

Oct 08, 2021
Human-centered design for AI; working with Fei-Fei Li; human first design for AI, Andrew Kondrich - The Data Scientist Show #006

Andrew Kondrich is a machine learning engineer at Scale. We talked about his career journey, human first design for AI, how to get into machine learning, and what kind of candidates companies are looking for.

Oct 01, 2021
From history major to data science manager, when you shouldn't use data, Bryan Davis - The Data Scientist Show #005

Bryan is a data science manager, previously he worked at Facebook and Indeed as senior data scientist. Bryan specialize in ad system design, ad ranking, and A/B testing platforms. 

We talked about: 

- how he got into data science as a history major 

- when not to use data science to make decisions 

- how data scientists should influence the company's culture 

- how data scientists can have a competitive edge in the future 

- what is the ad ranking problem 

- data science books for game theories 

- how to use game theories in real life  

You can also listen to this episode on Apple podcast and Spotify. 

You can also watch this episode on YouTube:

Sep 24, 2021
How to get your dream job without applying online. with Jerry Lee - The Data Scientist Show #004

Jerry is the COO/Founder of Wonsulting and an ex-Senior Strategy & Operations Manager at Google & used to lead Product Strategy at Lucid. After graduating from Babson College, Jerry was hired as the youngest analyst in his organization by being promoted multiple times in 2 years to his current position in Google. With Wonsulting, Jerry partners with universities & organizations (220+ to date) to help others land into their dream careers. He's amassed 250,000+ followers across LinkedIn, TikTok & Instagram and has reached 40M+ professionals. In addition, his work has been featured on Forbes, Newsweek, Business Insider, Yahoo! News, LinkedIn & elected as the 2020 LinkedIn Top Voice for Tech.

Jerry shared his expert advice on how to network effectively, how to send messages to recruiters, and how he used data analytics to solve million dollar business problems.

Sep 17, 2021
Transition into machine learning as an engineer, 2 mistakes ML scientists should avoid. Alexey Grigorev - The Data Scientist Show #003

Alexey Grigorev is a principal data scientist at OLX Group, He is also the founder of Data Talks Club with 4,100 members. He wrote a book called "Machine Learning Bookcamp" to help people learn machine learning by doing projects.

We talked about: how Alexey transitioned into machine learning

- What kind of project helped him get his job

- 2 mistakes new data scientists often make

- Why do you need to know the baseline 

- What makes you stand out as a candidate 

- His free machine learning course     

Subscribe to the channel for weekly interviews with data scientists and AI researchers! 

This episode is also available on YouTube:

  #datascience #machinelearning #ai #ml #career

Sep 08, 2021
The future of data scientists; network like a champion with Jim Zheng - The Data Scientist Show #002

Jim Zheng is an engineering manager at Flexport, building the data platform; he was a data scientist at Salesforce, worked at Yahoo as a UX designer, and was a researcher in computer science at Stanford. He is also the cofounder of Senpai, an audio platform for experts to share domain knowledge.  Ask Jim a question on Senpai:

Jim's article on how to send cold emails: 

We talked about:

- Jim's career path in engineering and data science

- What makes a great data scientist 

- What's the future of data scientists 

- What's a 'human cloud' 

- How to network like a champion 

- Best way to work with mentors 

- Career advice to his younger self  

- Life lessons he learned from playing chess  

Follow Daliana on Twitter and Linkedin to get updates about the show. 

Subscribe to the channel for weekly interviews on data science and AI!  

This episode is also available on YouTube

Sep 03, 2021
Build resilient ML models; advice for ML careers - Gerald Friedland The Data Scientist Show #001

Gerald Friedland is the CTO of an Brainome and professor at UC Berkeley. Listen to his advice on how to build more resilient machine learning models and get inspired from his career journey! We covered:

- how did he get into machine learning

- what's the biggest problem with the current machine learning trend

- how to make ML models more resilient and avoid overfitting

- how should people learn if they want to be better at machine learning

- how Gerald built a tech company in college

- his secret of being innovative

His class is here:

His YouTube lectures from last year online:

Information Theory, Inference, and Learning Algorithms (the book Gerald mentioned):

Follow Daliana on Twitter and Linkedin to get updates about the show!

Aug 30, 2021