Sundas Khalid

Co-Founder

Seattle, Washington, United States11 yrs 8 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Led Google Search Engine analytics as Principal Analytical Lead.
Negotiated $1.4M in job offers for women of color in tech.
Featured in Forbes for resilience and advocacy in education.

Stackforce AI infers this person is a Data Science and Analytics expert in E-Commerce.

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Skills

Core Skills

Data ScienceAnalyticsEntrepreneurshipExperimentationData EngineeringData AnalysisWeb Analytics

Other Skills

PythonR (Programming Language)MentoringA/B TestingStatisticsBig DataGooglingEdtechEducational TechnologyInfluencer MarketingPeople ManagementTeachingProduct AnalyticsMachine LearningArtificial Intelligence (AI)

About

👋 Hi , thank you for visiting my LinkedIn. My name is Sundas Khalid. I currently work at Google as Principal Analytical Lead, leading Google Search Engine analytics. Prior to Google, I was a Data Scientist at Amazon where I received awards for my work as a data science leader driving large-scale experimentations and data science initiatives. My story of resilience was featured on Forbes (see Featured section to read the article). As the first-female in my family to graduate university, I am an advocate of women's education and workforce diversity, and actively participate in diversity, equity & inclusion within and outside of Google. I enjoy public speaking and have spoken at +50 talks to an audience of over 100,000. In my free time, I enjoy creating educational content on various platforms on data science, career and financial literacy. One of my 2021 goals was to help WOC in tech negotiate job offers by $1M and I completed that goal with $1.4M negotiated in 2021. 📝 Signup for my newsletter: blog.sundaskhalid.com 🔗 All the links in one place: sundaskhalid.com/links 📧 Business inquires at team@sundaskhalid.com All views are mine.

Experience

Google

Principal Analytics Lead - Google Search Ads

Dec 2019 – Present · 6 yrs 3 mos · Greater Seattle Area

Billions of users use Google Search Engine daily to find information, and I am very proud of my current work in search engine space.
20% Projects:
Data Science Faculty: teaching Googlers data science fundamentals
Experimentation Lead: building large scale solutions to amplify experimentation at scale
People Pillar Lead: leading conversations and initiatives on outreach and recruitment
IamRemarkable Lead: facilitate and propose self-promotion workshops especially for underrepresented groups

Data SciencePythonAnalytics

Sk media

Founder

Jan 2019 – Present · 7 yrs 2 mos · Greater Seattle Area

EntrepreneurshipData Science

Amazon

3 roles

Data Scientist, Experimentation (Weblab Science)

Promoted

Jul 2016 – Dec 2019 · 3 yrs 5 mos

I powered Amazon's worldwide A/B testing platform with analytics and statistical insights to understand customer behavior that enables business stakeholders to make million-dollar, highly critical launch decisions at the click of a button.
Projects:
Baseline Imbalance - Population Bias in Weblab (A/B test): September 2016
Weblab (A/B test) Monetization - ROI Portfolio Analysis: February 2017
Pre-Trigger Alarm Detection in Weblab (A/B test): March 2017
Pre-Trigger Alarm Mitigation in Weblab (A/B test): Jan 2018
Weblab On-Demand: Created technical framework for new metrics onboarding and method prototyping. Initial product launch (Nov 2017) had 19 metrics from 6 teams, including Amazon Alexa, Video, and Payments. Current queue (Jan 2018) has 21+ metrics from 13 teams awaiting to on-board, including Amazon Music, A9, and Checkout.
Active Weblab (A/B test) Bar Raiser. Training future bar raisers via 1-on-1 and group sessions.
Experimentation for non-prime customers: 2018
Hybrid (parallel) Experiments: 2019
Holdout Experiment: advanced & long-term experimentation: 2019
Presentations:
Wo[men] of CXT - Grace Hopper Edition: November 2016
Grace Hopper Celebration Takeaways CXT: October 2017
Weblab A/B test Monetization: May 2017
Weblab A/B test Training for Twitch Prime: November 2017
Bar Raiser Training for A/B testing - Consumer Electronics Tech: (multiple sessions) Jan 2018
Statistics 101 for A/B testing: Jan 2018
Weblab A/B test 101 for A9 (Amazon Search): Jan 2018
Weblab A/B test On-Demand Metrics: Jan 2018
Statistics 101 for A/B testing - Alexa: Feb 2018
Weblab Analytics Deep-Dive - Community Shopping: July 2018
Weblab Analytics for Amazon Echo: September 2018
Machine Learning University Courses:
Introduction to Machine Learning at Amazon (IMLA)
Mathematical Fundamentals for Machine Learning (MATH)
Introduction to Data Science (DATA)
Regression for Machine Learning (REGR)

R (Programming Language)MentoringData ScienceExperimentation

Data Engineer, Worldwide Traffic

Jul 2014 – Jun 2016 · 1 yr 11 mos

Data Mart: Engineered base infrastructure to develop Oracle CUBE in ETL to provide multidimensional visibility into Recognized Customer Visits (by Mobile, Traffic Channels, Prime/Non-Prime, Product Category etc.) from clickstream data—led 4 presentations for business and technical community.
Data Modeling: Designed data architecture to capture top 20 High Value Actions (HVA). HVA is any action that maximizes a customer’s lifetime value as defined by DSI (1st Prime/Student/Mom Signup, 1st Amazon Smile Purchase, 1st Mobile App Sign-in etc.). Centralized HVA data repository for all geographies worldwide.
Reporting: Proposed and redefined Investor Relations “active customer” reports. These numbers are shared with external Amazon shareholders at the quarterly earning calls by Jeff Wilke, CEO of Worldwide Consumer.
Identified new KPIs and managed WBR/MBR/QBR and Investor Relation reporting (S-team goal) for 13+ countries to support 1.3 billion annual marketing spend, and led high-priority deep-dives to root cause data quality issues.
Presentations:
2015 Traffic and Consumer Analytics Boot Camp (business audience):Presenter
Data Engineering Meet-up (technical audience): Presenter
Traffic Managers Meet-up Q1-2015 (business audience): Presenter
Traffic Managers Meet-up Q3-2014 (business audience): Presenter

Data AnalysisBig DataData Engineering

Data Analyst Intern, Worldwide Traffic

Sep 2013 – Apr 2014 · 7 mos · Greater Seattle Area

Utilized Excel, VBA, SQL, Perl, ETL, and other business intelligence systems to analyze traffic metrics and measure channel effectiveness through which customers enter Amazon.com and global websites
Coded a 300+ lines Excel VBA macro to restructure and automate the WBR process, saving 60-90 min/weekly to meet a 7 hour deadline on Mondays
Reduced data delays by 30% and improved data accuracy by optimizing the monitoring and validation processes
Created AmazonSmile WBR deck using Excel and PivotTables to report weekly traffic metrics for management review
Performed data analysis on AmazonSmile customers, providing in-depth visibility into customer purchasing behavior that directed marketing initiatives to improve customer retention—earning 1st place among 40 intern presentations

Data AnalysisBig Data

Utrip, inc.

Web Analytics Intern

Feb 2013 – Apr 2013 · 2 mos · Greater Seattle Area

Identified KPIs and implemented Google Analytics dashboards, saving the team 104 hours of repetitive work annually
Analyzed company’s web traffic and blocked internal IP addresses tracking to increase reports’ accuracy
Presented a Google Analytics crash course to Utrip executives and created a 5+ page report for future reference

Data AnalysisGooglingWeb Analytics