Sara is available for hire
Hire SaraSara Song
Verified Expert in Engineering
Data Scientist and Developer
San Francisco, CA, United States
Toptal member since July 14, 2026
Bio
Sara is a data and product analytics professional with 9+ years of experience turning complex data into actionable business insights. Her expertise includes SQL, Python, A/B testing, funnel analysis, user segmentation, retention, forecasting, dashboards, and statistical modeling. Sara helps teams improve product performance, customer engagement, and revenue through clear analysis, scalable data solutions, and practical recommendations.
Portfolio
Weave communcation
Python 3, SQL, Data Build Tool (dbt), A/B Testing, Churn Analysis...
BENlabs
A/B Testing, Python, Churn Analysis, Linear Regression, Hypothesis Testing...
Twilio
Machine Learning, A/B Testing, SQL, Linear Regression, Python...
Experience
- Tableau - 8 years
- Streamlit - 8 years
- Data Science - 8 years
- Product Analytics - 8 years
- SQL - 8 years
- Data Process - 8 years
- PostgreSQL - 6 years
- Python 3 - 4 years
Preferred Environment
Python 3, PostgreSQL, Streamlit, Tableau
The most amazing...
...thing I've done is work within a growth team to improve the new signup and subscriptions by 25%.
Work Experience
Lead Product Analyst – AI, Fintech, & Core
2024 - 2026
Weave communcation
- Owned analytics for the company’s first AI product, delivering $600,000+ in savings, increasing adoption from 50% to 75%, and reducing churn from 20% to 5% through recommendation modeling and customer analysis.
- Built an AI-powered product dashboard used by 5 PMs and 15+ engineers to surface customer pain points and accelerate decision-making.
- Analyzed support cases around the new platform release and identified release process issues. Reduced support cases by 25% and increased the net promoter score (NPS) by 30%.
Technologies: Python 3, SQL, Data Build Tool (dbt), A/B Testing, Churn Analysis, Linear Regression, Python, Hypothesis Testing, Large-scale Data Processing, Logistic Regression
Lead Product Analyst
2021 - 2024
BENlabs
- Managed a team of 5 analysts, mentored 4 junior analysts, and led the hiring of 1 new member.
- Built a data research lab, hired 2 analysts, reduced churn by 15%, increased ratings by 60% and tool usage by 14%, and launched the company’s first ML recommendation engine with OpenAI.
- Led cross-functional analytics, increasing subscriptions by 30% and adoption by 20%, while standardizing KPIs and A/B testing practices.
Technologies: A/B Testing, Python, Churn Analysis, Linear Regression, Hypothesis Testing, Large-scale Data Processing, Logistic Regression
Senior BI Advanced Analyst
2021 - 2021
Twilio
- Proposed, designed, and tested new time series machine learning methodologies to build a data quality alert system, achieving 90% precision and 90% recall on testing results.
- Used machine learning-driven analysis and A/B testing to understand historic patterns of new voice customer acquisition and growth value of self-service versus sales-assistance customers.
- Used advanced SQL queries to analyze and provide insights on how to reopen the office properly, with reports built in Tableau in collaboration with multiple teams.
Technologies: Machine Learning, A/B Testing, SQL, Linear Regression, Python, Hypothesis Testing, Large-scale Data Processing, Logistic Regression, Forecasting
Senior Data Scientist
2018 - 2021
DigiCert
- Led data-mining project to group 310,000 customers using unsupervised clustering by product use and market share, identifying high-value clusters for targeted marketing efforts.
- Forecasted customer retention with boosting and classification predictive analytics, achieving 70% precision and 90% accuracy—used monthly by the sales team.
- Led project to diagnose and fix major issues in Salesforce/Oracle data pipeline, identifying $1.6 million in uncollected revenue with a cross-departmental team of thirteen members.
- Responded to a security event affecting 50,000 customers using Python automation, coordinating the data engineering team under a strict deadline for the CEO and EVPs.
- Developed and deployed an automated staff needs forecast using Facebook Prophet and the SARIMA model with a daily forecast within 2% error—used daily for employee task assignment.
- Used A/B testing, statistical modeling, and power analysis to optimize $3 million annual digital marketing spend, increasing ad impact by 30% and decreasing cost by 40%.
- Analyzed over $120 million of 2020 customer retention opportunities, reporting to the CEO/CFO—used in developing the business plan.
- Combined 5 system databases into a single data mart, reducing data renewal time by 20x—used company-wide by 1,600+ employees.
Technologies: Python, A/B Testing, SARIMA, Statistical Modeling, Clustering, Churn Analysis, Linear Regression, Large-scale Data Processing, Logistic Regression, Forecasting
Experience
Personal Spending Analyzer
https://github.com/sarasdsutah/AI-Data-Assistant/tree/main/knowledgeBuilt an AI-powered personal spending analyzer that helps users understand spending patterns, evaluate credit card rewards, and make better financial decisions. The app allows users to upload transaction CSV files or credit card statements, automatically categorizes expenses, and generates personalized insights within seconds.
I designed the product workflow, analytical logic, and recommendation framework, including cashback optimization, card comparison, spending trend analysis, and scenario modeling. The app can determine whether a user’s current credit cards align with their spending habits and recommend alternatives based on potential rewards and personal preferences.
I also integrated AI to answer natural-language questions about transactions and explain financial trade-offs in a clear, practical way. To improve reliability, I developed structured business rules, formulas, and user-specific knowledge files so recommendations are based on defined assumptions rather than generic AI responses.
Technologies used include Python, OpenAI, Streamlit, data visualization, financial modeling, and automated document processing.
I designed the product workflow, analytical logic, and recommendation framework, including cashback optimization, card comparison, spending trend analysis, and scenario modeling. The app can determine whether a user’s current credit cards align with their spending habits and recommend alternatives based on potential rewards and personal preferences.
I also integrated AI to answer natural-language questions about transactions and explain financial trade-offs in a clear, practical way. To improve reliability, I developed structured business rules, formulas, and user-specific knowledge files so recommendations are based on defined assumptions rather than generic AI responses.
Technologies used include Python, OpenAI, Streamlit, data visualization, financial modeling, and automated document processing.
Education
2018 - 2018
Master's Degree in Business Analytics
University of Utah - Salt Lake City, UT, USA
Certifications
AUGUST 2023 - PRESENT
Applied Data Science Program
MIT Professional Education
Skills
Tools
Tableau
Frameworks
Streamlit
Storage
PostgreSQL
Languages
Python 3, SQL, Python
Other
Data Process, Data Science, Product Analytics, A/B Testing, Churn Analysis, Linear Regression, Hypothesis Testing, Large-scale Data Processing, Logistic Regression, Forecasting, Data Modeling, Data Build Tool (dbt)
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