Siang Kong Email & Phone Number
@shipt.com
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Who is Siang Kong? Overview
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Siang Kong is listed as Senior Data Scientist, Machine Learning at Shipt, a company with 6496 employees, based in San Francisco, California, United States. AeroLeads shows a work email signal at shipt.com and a matched LinkedIn profile for Siang Kong.
Siang Kong previously worked as Senior Machine Learning Engineer at Shipt and Data Scientist, Machine Learning at Shipt. Siang Kong holds Summer Program In Quantitative Methods Of Social Research from University Of Michigan.
Email format at Shipt
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AeroLeads found 1 current-domain work email signal for Siang Kong. Compare company email patterns before reaching out.
About Siang Kong
Siang Kong is a Senior Data Scientist, Machine Learning at Shipt. They possess expertise in python, r, quantitative analytics, econometrics, machine learning and 35 more skills. Colleagues describe them as "Siang is a very smart person and so kind team member when I worked with her. We had many data analysis projects such as predict model, PCA model, decision tree, she showed her talent about them. It was my pleasure that worked with Siang. She always keeps concentrate and positive in her duty. I highly recommend her."
Listed skills include Python, R, Quantitative Analytics, Econometrics, and 36 others.
Siang Kong's current company
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Siang Kong work experience
A career timeline built from the work history available for this profile.
Data Scientist, Machine Learning
- Applying Machine Learning to optimize various focus areas:
- Search Query Understanding
- Catalog Enrichment
- Recommendation Systems
Data Scientist
- Media Mix Modeling - Maintained an in-house media mix model using Bayesian Time Series models. Inform budgeting decisions and forecast order volume for marketing and finance stakeholders. Researched marketing theories.
- Supply Chain Dashboard - Created the first dashboard for the supply chain monitoring through a new ETL job driven by Python and SQL to automate reports, which freed up 30+ labor hours per week. Defining metrics and.
- Ad-hoc Analysis - Initializing analytics projects to detect hidden problems and solutions with data for cross-functional teams.
Machine Learning Intern
- Applied Machine Learning techniques to classify brain activities after different memory tasks on 35 GB+ functional MRI data in Python.
- Generated heat maps for brain and examined whether functional brain networks demonstrate stronger complex memory retrieval in young adults.
- Created a custom Python module to automate feature engineering based on PyMVPA, a Python library for fMRI data, and Scikit-learn to improve readability and efficiency of scripts.* Based on the previous work of Wais PE.
Data Scientist
- Addressed overstock/ out of stock inventory issues with a data-driven strategy.
- Predicted future sales volume by scrapping Amazon Ranking data in Python.
- Reduced over-orders by 40% by revising sales forecast using SARIMA time series models.
- Optimized production order to satisfy shipping and order goals.
- Adjusted budget for the global marketing team with Total Addressable Market analysis on medical instruments.
Research Assistant
- Created reports on KPMG FinTech 100 for financial technology studies.
- Conducted researches and put up report for fund-raise for Chang-Hua Christian Hospital, the pioneer hospital in Taiwan that develops precision medicine.
Assistant Researcher
- Advisor: Professor Shu-Jen Yeh
- Translated agricultural data in 1895-1945 from Japanese and built database in excel to study the correlation between the growth of rice and sugar cane; drew economics models using Excel and CorelDraw
Colleagues at Shipt
Other employees you can reach at shipt.com. View company contacts for 6496 employees →
C John Klehm
Colleague at Shipt
Greater Birmingham, Alabama Area, United States, United States
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C(
Carly (Stoddart) Young
Colleague at Shipt
Greater Birmingham, Alabama Area, United States
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TG
Tanya Goldbloom
Colleague at Shipt
Circle Pines, Minnesota, United States, United States
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TB
Tiffany Bramlette
Colleague at Shipt
Tucson, Arizona, United States, United States
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TM
Tyeisha Miles
Colleague at Shipt
Columbus, Ohio Metropolitan Area, United States
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AD
Angela Draeger
Colleague at Shipt
Eau Claire, Wisconsin, United States, United States
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BW
Brianna Willis
Colleague at Shipt
Birmingham, Alabama, United States, United States
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JF
Jocelyn Fortier
Colleague at Shipt
Lehi, Utah, United States, United States
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DN
Den Nghia
Colleague at Shipt
Quận 7, Ho Chi Minh City, Vietnam, Viet Nam
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KM
Kimberly Mackay
Colleague at Shipt
Summerville, South Carolina, United States, United States
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Siang Kong education
Summer Program In Quantitative Methods Of Social Research
Master Of Science - Ms, Data Science
Bachelor Of Arts - Ba, Economics
Frequently asked questions about Siang Kong
Quick answers generated from the profile data available on this page.
What company does Siang Kong work for?
Siang Kong works for Shipt.
What is Siang Kong's role at Shipt?
Siang Kong is listed as Senior Data Scientist, Machine Learning at Shipt.
What is Siang Kong's email address?
AeroLeads has found 1 work email signal at @shipt.com for Siang Kong at Shipt.
Where is Siang Kong based?
Siang Kong is based in San Francisco, California, United States while working with Shipt.
What companies has Siang Kong worked for?
Siang Kong has worked for Shipt, Thirdlove, Ucsf Medical Center, Mdf Instruments Usa, and Fcc Partners (Taipei).
Who are Siang Kong's colleagues at Shipt?
Siang Kong's colleagues at Shipt include C John Klehm, Carly (Stoddart) Young, Tanya Goldbloom, Tiffany Bramlette, and Tyeisha Miles.
How can I contact Siang Kong?
You can use AeroLeads to view verified contact signals for Siang Kong at Shipt, including work email, phone, and LinkedIn data when available.
What schools did Siang Kong attend?
Siang Kong holds Summer Program In Quantitative Methods Of Social Research from University Of Michigan.
What skills is Siang Kong known for?
Siang Kong is listed with skills including Python, R, Quantitative Analytics, Econometrics, Machine Learning, Statistics, Time Series Analysis, and Deep Learning.
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