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: 49
Reviews: 0


A deep dive into data scientists' day-to-day work, tools and models they use, how they tackle problems, and their career journeys. This podcast helps you grow a successful career in data science. Listening to an episode is like having lunch with an experienced mentor. Guests are data science practitioners from various industries, AI researchers, economists, and CTOs of AI companies. This is hosted by Daliana Liu, senior data scientist. Follow Daliana on Twitter( for more updates on data science, career, and this podcast.

Episode Date
Using AI to detect online abuse, from physics PhD to staff ML engineer@Linkedin, persuasion at work with James Verbus - the data scientist show #035

(Timestamps below) James Verbus is Staff Machine Learning Engineer at LinkedIn. He has a PhD in Physics from Brown university. He is the tech lead of the Anti-Scraping and Automation AI Team, working on protecting LinkedIn's Members from bots and abusive scripted behavior, pioneering the use of deep learning to detect abusive automated sequences of user activity (blog post). 

(00:01:14) from physic to data science 

(00:16:37) background of online abuse detection 

(00:24:40) Isolation Forest Algorithm

(00:42:59) his day-to-day as a staff ML Engineer 

(00:52:57) how to persuade stakeholders 

(00:58:17) how to build influence at work 

(01:00:22) how he grew to staff engineer 

(01:13:48) what he learned from his mentor 

Follow Daliana on Twitter @DalianaLiu for more on data science and this podcast. Subscribe to the channel and leave a 5-star review if you like this episode :)

May 10, 2022
The golden age of AI and neuroscience, brain computer interface (BCI), from academia to FAANG with Patrick Mineault - The Data Scientist Show #034

(Timestamps below) Patrick Mineault is a neural data scientist. He has worked at Google and Facebook after he did a postdoc at UCLA. He worked on Brain Computer Interface (BCI) at Facebook Reality Labs, building a BCI that allows you to type with your brain. He tweets about neuro-AI @patrickmineault, and writes a blog ( sharing his career journey and learnings along the way.

How he got into data science (00:02:41)

His work at Google on A/B testing (00:04:17)

How he joined Facebook Reality Lab(00:23:53)

Projects on neuro-AI and brain computer interface (BCI) (00:27:13)

Skills needed for BCI research (00:34:37)

How AI influence neuroscience (01:34:28)

computer vision VS human vision (01:39:57)

model vs data, nature vs nurture(01:45:32)

If you enjoy the show, subscribe and give me a five star review!

Follow Daliana on Twitter @DalianaLiu for more on data science and this podcast.

May 05, 2022
From biostatistician to the 'artist of data science', how he turned his life around, philosophy - Harpreet Sahota - The Data Scientist Show#033

Harpreet Sahota is a data scientist and ML developer advocate, he is also the host of “artist of the data science” podcast and weekly data science happy hours, he is the principal data science mentor at data science dream job. He is also a philosophy nerd. He had some struggles when he tried to get into data science, and today we’ll talk about his experience as a biostatistician, data scientist, lessons he learned from his journey and from mentoring other people, and how he turned his life around.  

Follow @DalianaLiu for more on data science and this podcast. Give me a 5-star review if you find the show helpful :)

Harpreet's Linkedin:

The artist of data science podcast:

Apr 06, 2022
How he built the best Covid forecasting model, lessons learned and how to improve model performance with Youyang Gu - The Data Scientist Show#032

Youyang Gu is the creator of In 2020, while most Covid prediction model failed, without any experience in medicine he created a forecasting model that outperforms almost all medical experts. Yann LeCun, Facebook's chief AI scientist and professor stated that Gu's model "is the most accurate to predict deaths from COVID-19", surpassing the accuracy of the well-funded Institute for Health Metrics and Evaluation COVID model. It was cited by the Centers for Disease Control (CDC) in its estimates for U.S. recovery.

Currently, he is a member of the Technical Advisory Group at the World Health Organization. Working on laying the groundwork for a comprehensive, global study to document and analyze differences in levels of mortality attributable to COVID-19 between and within countries.

Today we talked about how he built the model, lessons he learned, his advice for data scientists and what his working on today. 

Youyang's blog:

Youyang's Twitter:

If you like the show, subscribe and give me a five-star review :) Follow @DalianaLiu for more on data science and this podcast. 

Mar 31, 2022
Feature engineering, ML models in production, new trend for ML tools, day-to-day of a principal engineer with Willem Pienaar - The Data Scientist Show #031

Willem is the creator of Feast, an open-source feature store (, building tools at the intersection of engineering, data, and ML. Currently, he work as a Principal engineer at Tecton, Leading the development of Feast, an open source feature store. Previously, he has worked in South Africa, Thailand, Singapore before he moved to San Francisco in the US. Today we’ll talk about machine learning in production, cool projects he worked, machine learning in startup and how to pick the right data science track for your career.

Follow Daliana @DalianaLiu for more on data science and this podcast. Give me a 5-star review if you enjoy the show :)

Willem's Linkedin:

Mar 24, 2022
Machine learning in healthcare, how to scale ML solutions, from ML researcher to product leader at Microsoft with Muazma Zahid - The Data Scientist Show #030

Muazma Zahid is a leader in data and AI, speaker and researcher in Biomedical Engineering with several international publications and awards. We talked about machine learning in healthcare, how to scale data science solutions, her journey from a ML researcher to data engineer to engineering manager to a product leader. 

She joined Microsoft in 2018 as a data engineer, later became a senior manager in software engineering, and now she is a principal product manager. She won the mentor of the year award in 2020 by Women Tech Network. 

Subscribe to the channel and give us a 5-star review if you enjoy the show! Follow Daliana for more on data science and updates of this show on Twitter @DalianaLiu

Muazma's Linkedin:

Mar 20, 2022
Hands-on time series analysis, open source projects, R packages, MLOps common mistakes with Rami Krispin - The Data Scientist Show #029

Rami leads the data science and engineering team at Apple Finance Decision Support. He uses advanced statistical and machine learning models to help leadership make better decisions. He is also an open-source contributor and the author of Hands-On Time Series Analysis with R and several R packages for time series analysis and machine learning applications. He has a master degree in applied econometrics. We talked about time series, open source, MLOps and his career journey

Follow Daliana Liu on Twitter @DalianaLiu for more on data science and updates for this podcast. If you enjoy the show, give me a 5-star review!

Connect with Rami:





Mar 11, 2022
Becoming a deep learning researcher without a PhD, graph neural network(GNN), time series, recommender system with Kyle Kranen - The Data Scientist Show#028

Kyle Kranen is a Deep Learning Software Engineer at Nvidia. Researching, implementing, and optimizing state of the art distributed deep learning models, using mainly Pytorch and Tensorflow. He has a unique combination of skillset of both hardware and software engineering. We talked about Graph Neural Network (GNN), Temporal Fusion Transformer (TFT), time series, and other deep learning research topics and his career journey.  

Follow @dalianaliu for more on data science, career, and updates of this podcast.

Kyle's Linkedin:

Mar 03, 2022
How to 'predict' the past, geospatial data's use cases, Data-as-a-Service (DaaS), out-of-the-box career advice with the CEO of SafeGraph, Auren Hoffman - The Data Scientist Show #027

Auren Hoffman is CEO of SafeGraph: the place for data about physical places. We talked about how to use analytics and machine learning to find truth in data, geospatial data and their use cases, the impact of DaaS, and what he looks for when he develops talents. Auren's Twitter @auren.

Follow Daliana on Twitter @DalianaLiu for more updates on data science, career, and this podcast.

Feb 24, 2022
Telling compelling stories with data, people skills for analytical thinkers with Gilbert Eijkelenboom - The Data Scientist Show #026

Gilbert Eijkelenboom is the founder of Mindspeaking, a training program helping data & analytics professionals improve their business understanding, persuasion, and storytelling skills. He wrote the best-selling book “people skills for analytical people”. We talked about to get buy-in from stakeholders, how to build work relationships as introverts, how to earn trust, how to tell compelling stories with data, and lessons he learned from playing poker.

Follow Daliana on Twitter for more on data science, career, and this podcast.

Gilbert offers various free materials:

Feb 17, 2022
Sports analytics and personal branding for data scientists, Ken Jee - The Data Scientist Show #025

Ken Jee is the head of data science@Scouts Consulting Group and a YouTube creator with over 180k followers. Today we talked about sports analytics, how to grow your career and get promoted, how to explain complex concepts to stakeholders, how to build personal brands as data scientists.  

Subscribe to the show and I'll appreciate a comment or 5-star review if you find it helpful

Follow Daliana Liu on Twitter for more updates on data science, career, and this show. 

Ken Jee's Linkedin, YouTube.

Feb 09, 2022
From Apple store specialist to ML engineer at Apple, build a portfolio through open source projects, Julia Language, with Logan Kilpatrick - The Data Scientist Show #024

Logan Kilpatrick is a machine learning engineer at Apple, Developer Community Advocate of Julia. He is a teaching fellow at Harvard extension school, and currently doing a master program of science in Law. Today we’ll talk about how he became a Machine learning engineer, the internship he did in NASA, why you should care about open source communities, Julia, what the future of machine learning looks like, make sure you stay till the end. Logan's Twitter, Linkedin.

If you like the show, give me a 5-star and subscribe to the channel. Follow Daliana on Twitter for more updates on data science, career, and this podcast.

Feb 03, 2022
Tackling complex ML problems with small steps, MLOps best practices, pre-model analysis, from marketing analyst to principal ML researcher with Nathan Landi, The Data Scientist Show #023

Nathan Landi is a principal quantitative researcher at TEKSystems. He is on the advisory board of MLOps world. We talk about pre-model analysis using information value, MLOps best practices, multi-stage modeling, tackling complex problems with simple models, interview tips, and how he grew his career from marketing analyst to principal ML researcher.

The mentorship service mentioned is SharpestMinds, it's free to sign up here.

Nathan's Linkedin:

Jan 27, 2022
Data-driven sales strategies, sales metrics, how to collaborate with business leaders with Dennis Yu - The Data Scientist Show #022

Dennis Yu is a Revenue and Strategy Leader, currently he is the Merchant Success Team Lead at Shopify, he’s on the advisory board of USC startup accelerator, and he is also leading Talent and Professional Development for Asian ERG at Shopify.

Today we’ll talk about what business leaders look for in data science projects and his career journey.

  • Sales metrics: LTV GMV band, etc
  • Example of how he would grow sales revenue
  • How to tell the stories with data
  • How data scientists and business leaders should collaborate
    • His career journey
    • How growing up as an Asian American shaped his perspectives

Dennis's Linkedin:

Jan 20, 2022
Economic thinking and a must-listen mini MBA for data scientists with Airbnb VP and Wharton Professor, Amit Gandhi - The Data Scientist Show#021

Amit Gandhi is a technical fellow and VP at Airbnb. He is a professor in economics at the Wharton School in the University of Pennsylvania. He gave as a master class on economic thinking and a mini-MBA tailored for data scientists. We also talk about his career journey, decision-making, machine learning, economics, and his advice to data scientists, make sure you stick to the end. Please give this podcast a 5-star review if you find it helpful, thank you!

His Linkedin:

Jan 13, 2022
Translating ML model’s output into financial impact, fraud detection, financial modeling at Google, interview preparation with Dan Lee - The Data Scientist Show #020

Dan Lee is the an ex-Google data scientist turned founder of DataInterview - an interview prep platform for data scientist. We talked about how to translate model results into dollar amount, fraud detection models, quantitative thinking, data storytelling, best practices in exploratory data analysis (EDA), and interview prep tips.

His Linkedin:

Interview Prep:

Follow Daliana Liu on Twitter @DalianaLiu for more updates. Give this show a 5-star review if you enjoy it! 

Jan 05, 2022
Unlocking the power of emotional intelligence for your career success, how to handle toxic relationships and how to regulate negative emotions with Marc Brackett - The Data Scientist Show #019

Marc is a Yale Professor and the founding director of Yale Center for Emotional Intelligence. He wrote the best selling book “Permission to Feel”. Today we’ll talk about how we can use emotional intelligence to empower our careers:

  • how to regulate negative emotions
  • how to deal with toxic relationships at work
  • how to influence big stakeholders

Follow Daliana on Twitter @DalianaLiu for more updates about the show and career talks. Leave a 5-star review if you enjoy it! 

Dec 30, 2021
The ultimate data science interview landscape, three shifts in DS job search, common mistakes in interviews with Andrew Berry The Data Scientist Show #018

Andrew Berry is a data science educator at Lighthouse Labs. He has worked with over 100+ students from various backgrounds trying to transition into data science. He teaches data science, coaches aspiring data scientists, and design courses.

We talked about the shift in data science interviews, how to tackle coding interviews, future of job search, how to build your portfolio, interviews tips for big companies vs small companies, behavioral interviews vs technical interviews, how to write cold emails and more.

Andrew's Linkedin:

Dec 23, 2021
From unemployed to chief data scientist of multiple startups, machine learning prototyping, how to read people, overcoming life struggles with Matt Kirk, the data scientist show #017

Matt Kirk is Daliana's mentor, so it's a very special episode! Matt has been many things in his life: data scientist, software engineer, research analyst (quant), a founder, a c-level executive, and so on.  We talked about Matt’s unique career adventure, machine learning solutions he built for startups, how to read people and influence stakeholders, how to understand yourself, how to be productive and how he overcome his life struggles.

You can reach out to him: matt[at]matthewkirk[dot]com

Dec 15, 2021
The unique algorithm for compact and accurate machine learning models, no-code ML use cases and its impact on the future of data scientists with Blair Newman - The Data Scientist Show #016

Blair Newman is the CTO of Neuton AI. Neuton is a zero-code cloud platform that empowers users of any tech level to apply the best machine learning practices for solving real-world challenges faster.

We’ll talk about Neuton AI’s patented deep learning algorithm that doesn’t use back propagation, his career journey, no-code ML use cases, and how does no-code ML impact the future of data science.

Blair’s Linkedin:

Neuton AI:

Dec 09, 2021
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, two 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