Stay ConnectedI’m Daliana Liu, an ex-Amazon data scientist turned career coach and content creator with 300k followers on LinkedIn. I interview data science and AI practitioners on how they tackle practical problems and navigate career challenges. We cover both technical skills and soft skills. Each conversation is like having lunch with a mentor and friend.
I share more about my career adventure and the lessons I learned with 22k subscribers, join here: https://www.dalianaliu.blog/
Copyright: © Daliana Liu
Pan Wu is a senior manager of data science at Meta. We talked about why he moved from machine learning to product data science, projects he worked on at Uber, Linkedin, and Meta, and how he transitioned from IC to manager. Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science and career.
Pan’s LinkedIn: https://www.linkedin.com/in/panwu/
Daliana's Twitter: https://twitter.com/DalianaLiu
Daliana’s LinkedIn: https://www.linkedin.com/in/dalianaliu/
(00:00:00) Introduction
(00:01:30) Why he transitioned from MLE to product DS
(00:07:38) Meta data scientists skill sets
(00:15:49) When did his interest shifted from MLE to product DS
(00:18:04) Is MLE more respected?
(00:25:46) A/B testing deep dives in 3 steps
(00:28:21) Built a tool at Linkedin
(00:35:52) How to sell your project
(00:41:07) Junior vs senior data scientist
(00:43:24) From staff data scientist to manager
(00:45:18) Explore being a manager
(00:46:24) Cultures in Uber, Linkedin, TrueCar
(00:52:09) Data science over the past 10 year
(00:55:06) MLE vs DS fun and frustration
(00:57:26) Product DS reality
(00:59:10) Learning new skills
(01:01:39) Mistakes he made
(01:06:34) Future of data science
(01:08:04) Will data scientists be replaced by AI
(01:09:42) Three skills he looks for when hiring
Betty Zhang is a data scientist currently working at a cloud security company, previously she was a data scientist at Amazon Web Services. Today we’ll talk about her computer vision projects in Sports, data science use cases in cyber security, from business major to data scientist, what’s her experience working in startups vs big tech companies. Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science and career.
Betty’s Linkedin: https://www.linkedin.com/in/betty-zhang-0bb63731/
Daliana's Twitter: https://twitter.com/DalianaLiu
Daliana’s LinkedIn: https://www.linkedin.com/in/dalianaliu/
(00:00:00) Introduction
(00:01:21) Computer Vision Project in Sports at AWS
(00:12:28) Challenges in computer vision
(00:14:02) Time allocation for ML projects
(00:15:22) 3 key skills for computer vision
(00:17:20) From business analyst to ML engineer
(00:18:14) How she got her data scientist job through Linkedin
(00:21:32) How she got into Amazon
(00:22:17) Three tech skills needed during Amazon interviews
(00:26:11) Why she joined a Cyber Security startup
(00:27:22) Three cybersecurity use cases
(00:29:47) Anomaly detection
(00:30:40) ML for cybersecurity
(00:34:43) Tech stacks Amazon vs Startups
(00:39:35) Startups vs big tech
(00:45:56) Balance learning and impact
(00:48:35) Advice for new data scientists
Che Sharma came back to discuss toxic behaviors in experimentation culture and provide actionable advice on how to handle those situations, how to have rigor and integrity when designing and analyzing A/B tests.
Che was the 4th data scientist at Airbnb, later he joined Webflow as an early employee. In 2021 he founded Eppo, a next-gen A/B experimentation platform designed for modern data and product teams to run more trustworthy and advanced experiments. We talked about A/B testing best practices, A/B testing for ML models, and Che’s career journey.Reach out to Che: https://www.linkedin.com/in/chetanvsharma/
Jason Yosinski was a founding member of Uber AI Labs. He is also a co-founder of WinscapeAI a company dedicated to using custom sensor networks and machine learning to increase the efficiency and sustainability of wind farms. Jason holds a PhD in computer science from Cornell University. We talked about his experience at Uber AI, his research in deep learning, and ML for wind farms. Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science and career. Jason’s Website: https://yosinski.com/Jason’s LinkedIn: https://www.linkedin.com/in/jasonyosinski/Daliana's Twitter: https://twitter.com/DalianaLiuDaliana's LinkedIn: https://www.linkedin.com/in/dalianaliu
(00:00:00) Introduction(00:06:06) His advice for Uber ML teams(00:16:03) From research to industry(00:20:24) ML for wind farms(00:25:40) Metrics for wind energy prediction(00:29:23) Start with a small dataset(00:32:00) ML in academia vs. the industry(00:33:24) Do you need a PhD for ML?(00:38:14) Daliana's story about grad school(00:41:37) The value of a PhD(00:43:13) ML Collective(00:48:36) Technical communication(00:57:21) ML Skillsets(00:59:45) Future of machine learning(01:05:23) Personal development: Hoffman process(01:15:13) Do things that excites you
Jeff Li is a senior data scientist at Netflix, focusing on Ads forecast. Previously he was a data science manager at Spotify, worked on supply forecasting, demand forecasting, and data infrastructure. He studied business at the University of Southern California. We talked about Ads forecasting, career path as a manager vs IC, culture in Spotify vs Netflix vs Doordash.Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science and career. Jeff Li’s LinkedIn: https://www.linkedin.com/in/lijeffrey/ Daliana's Twitter: https://twitter.com/DalianaLiu Daliana's LinkedIn: https://www.linkedin.com/in/dalianaliu
(00:00:00) Introduction(00:00:45) Got into data science from poker and consulting(00:07:54) Ads forecasting at Netflix and Spotify(00:13:30) From IC to manager to IC(00:14:53) how to measure forecasting models(00:21:58) collaborating with stakeholders in sales(00:29:44) how he became an expert in ads forecasting(00:49:57) impact sizing at Doordash(00:57:34) Company culture differences (DoorDash, Spotify, Netflix)(01:12:47) how he wants to grow his career
Che Sharma was the 4th data scientist at Airbnb, later he joined Webflow as an early employee. In 2021 he founded Eppo, a next-gen A/B experimentation platform designed for modern data and product teams to run more trustworthy and advanced experiments. We talked about A/B testing best practices, A/B testing for ML models, and Che’s career journey. Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science and career.Che’s LinkedIn: https://www.linkedin.com/in/chetanvsharma/Try Eppo for A/B testing: https://www.geteppo.com/Daliana's Twitter: https://twitter.com/DalianaLiuDaliana's LinkedIn: https://www.linkedin.com/in/dalianaliu(00:00:00) Introduction(00:01:26) Getting started in data science at Airbnb(00:03:08) Keys to successful A/B testing(00:06:53) Interpreting and communicating A/B test results(00:15:00) A/B testing best practices testing machine learning models(00:41:39) Centralizing experiment analysis(00:53:46) Preparing data scientists for the future(00:59:33) Developing communication skills as a data scientist(01:08:43) Transitioning from individual contributor to manager(01:12:28) The future of experimentation
We talked about self-learning, productivity, how Tina navigates her career change and how she thinks AI could change the future of work.
Tina's YouTube: www.youtube.com/@TinaHuang1
Lonely Octopus: www.lonelyoctopus.com
Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science and career.
Tina Huang is a data scientist turned YouTube creator with 500k subscribers. She is the founder of Lonely Octopus, an online program helping people gain data science, AI, and freelancing skills. She originally studied pharmacology before transitioning into tech, completing a master's degree in computer science at UPenn.
(00:02:38) Transitioning from Data Science to Content Creation
(00:06:29) Preparing for Data Science Interviews
(00:10:59) Starting a YouTube Channel
(00:14:18) Building Multiple Income Streams
(00:17:35) Getting Started with AI Skills
(00:29:29) Advice for Starting YouTube
(00:34:47) Improving Storytelling Skills
(00:36:58) Overcoming Procrastination
(00:42:33) The Future of Work
(01:47:08) Looking to the Future
(01:26:49) Income Breakdown
Vikram is the co-founder of Galileo – an AI diagnostics and explainability platform used by data science teams building NLP, LLMs and Computer Vision models across the Fortune 500 and high growth startups. Prior to Galileo, Vikram led Product Management at Google AI, where his team built models for the Fortune 2000 across retail, financial services, healthcare and contact centers. He has a master degree from Carnegie Mellon University from the school of computer science. If you enjoy the show, subscribe to the channel and leave a 5-star review. Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science and career.
Resources:LLM Studio: https://www.rungalileo.io/blog/announcing-llm-studio
Galileo: https://www.rungalileo.io/
Blog on LLM Hallucination: https://thesequence.substack.com/p/guest-post-stop-hallucinations-from
Vikram Chatterji’s LinkedIn: https://www.linkedin.com/in/vikram-chatterji/
"The Mom Test": https://www.amazon.com/The-Mom-Test-Rob-Fitzpatrick-audiobook/dp/B07RJZKZ7F
Daliana's Twitter: https://twitter.com/DalianaLiu
Daliana's LinkedIn: https://www.linkedin.com/in/dalianaliu
(00:00:00) Introduction
(00:04:24) How he got into machine learning
(00:06:53) Diagnosing large language models
(00:09:56) Addressing model hallucination
(00:12:46) Metrics for measuring hallucination
(00:17:30) From Google AI to starting Galileo
(00:24:08) Developing LLMs and putting them into production
(00:32:51) Galileo's diagnostics and explainability platform
(00:43:16) Advice for data scientists when joining a startup
Max Pumperla designed his own career path in data science. He is a freelance software engineer at AnyScale, and also a data science professor. We talked about reinforcement learning, open source contributions, Ray for data scientists, and his view on the data scientists role. If you enjoy the show, subscribe to the channel and leave a 5-star review. Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science and career.
Max’s LinkedIn: https://www.linkedin.com/in/max-pumperla-a8099354/
Max's GitHub: https://github.com/maxpumperla
Daliana's Twitter: https://twitter.com/DalianaLiu
Daliana's LinkedIn: https://www.linkedin.com/in/dalianaliu
(00:00:00) Introduction
(00:09:19) How he got a remote job through Twitter
(00:14:06) Introduction to Ray
(00:18:52) Reinforcement learning
(00:23:56) Key lessons on integrating customer feedback
(00:35:12) Flaws in data science job titles
(00:45:51) How to be irreplaceable as a data scientist
(00:48:55) An unconventional career path as a data scientist
(01:12:24) Productivity and work-life balance
(01:28:10) Advice for building a personal brand
Piero Molino was one of the founding members of Uber AI Labs. He worked on several deployed ML systems, including an NLP model for Customer Support, and the Uber Eats Recommender System. He is the author of Ludwig , an open source declarative deep learning framework. In 2021 he co-founded Predibase, the low-code declarative machine learning platform built on top of Ludwig.Piero's LinkedIn: https://www.linkedin.com/in/pieromolino
Predibase free access: bit.ly/3PCeqqw
Daliana's Twitter: https://twitter.com/DalianaLiu
Daliana's LinkedIn: https://www.linkedin.com/in/dalianaliu
(00:00:00) Introduction
(00:01:54) Journey to machine learning
(00:03:51) Recommending system at Uber Eats
(00:04:13) Projects at Uber AI
(00:09:34) Uber's customer obsession ticket system
(00:16:01) How to evaluate online-offline business and model performance metrics
(00:17:16) Customer Satisfaction
(00:28:38) When do you know whether a project is good enough
(00:41:50) Declarative machine learning and Ludwig
(00:45:32) Ludwig vs AutoML
(00:54:44) Working with Professor Chris Re
(00:58:32) Why he started Predibase
(01:07:56) LLM and GenAI
(01:10:17) Challenges for LLMs
(01:22:36) Advice for data scientists
(01:34:29) Career advice to his younger self
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