The Data Scientist Show

Jess Ramos is a Senior Data Analyst at Crunchbase, a LinkedIn Learning Instructor, and a content creator in the data space. She has a bachelor's degree in Math, Spanish, and Business from Berry University and a master's in Business Analytics from University of Georgia. Today we’ll talk about SQL in the real world, data analyst vs data scientist, is job hopping bad, how she negotiated her salary. Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science and career.Jess’ Linkedin: https://www.linkedin.com/in/jessramosmsba/

Preparing to Get a Job in Data Analytics: shorturl.at/sCNPT

Solve Real-World Data Problems with SQL: https://bit.ly/3Zq6wnd

Big Data Energy Newsletter: https://bit.ly/46x4rIR

Daliana's Twitter: https://twitter.com/DalianaLiuDaliana’s LinkedIn: https://www.linkedin.com/in/dalianaliu/(00:00:00) Introduction(00:01:24) Why Jess left her job at Freddie Mac(00:03:25) Is job hopping bad(00:04:42) How to explain short job stints when interviewing(00:06:49) Jess's day-to-day work and tech stack(00:09:15) SQL in the real world(00:12:10) How to talk data to stakeholders(00:18:33) How Jess prepares for SQL interviews(00:28:11) Data analysts vs data scientists(00:32:11) Choosing a career path(00:47:19) How to ask recruiter questions(00:50:15) Jess's LinkedIn content creation journey(00:59:03) The future of Jess's career(01:03:42) Jess's favorite books

Mehdi Noori is an applied science manager at the Generative AI Innovation Center at Amazon. I used to work with Mehdi while we were at the Machine Learning Solutions Lab at AWS. So before Amazon, Mehdi was a data scientist working on marketing intelligence. Mehdi has a PhD from University of Central Florida in civil engineering and sustainability. Subscribe to Daliana's newsletter for more on data science and career www.dalianaliu.com

Mehdi Noori: https://www.linkedin.com/in/mehdi-noori/

Predicting Soccer Goals: https://aws.amazon.com/blogs/machine-learning/predicting-soccer-goals-in-near-real-time-using-computer-vision/

My friend Misty moved to a farm in Portugal after her 20 years of career in finance. We talked about her experience moving from the busy corporate life to the farm life where she does a lot of manual work. Was it challenging, how does her finance work, and what is her advice to other people who also want to explore a different path outside of the modern city life. I hope this episode will give you a different perspective about your career.

Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science and career.Daliana's Twitter: https://twitter.com/DalianaLiuDaliana’s LinkedIn: https://www.linkedin.com/in/dalianaliu/

(00:00:00) Introduction

(00:11:41) Life on the farm

(00:15:46) Her finance plans

(00:22:55) Her career journey

(00:27:14) What do accountants do

(00:32:29) I thought I would be happy

(00:41:25) Daliana's personal view about finance; when it's enough for you

(00:44:41) Does she feel lonely on a farm?

(00:48:39) What if she didn't leave the corporate world?

(00:54:07) Does she regret her decision

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

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