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Senior Data Science and Product Management leader working with data-driven ML products in HR tech, advertising and geospatial analytics.EXPERIENCE- Senior Product Manager, Data @ Indeed.comSets and executes strategy for measuring who gets hired on Indeed, spearheading novel data collection efforts and using the data to build and deploy models across Indeed surfaces, leading a team of 12 Data Scientists, Engineers and APMs- Senior Product Manager (Data), SafeGraph (Series B startup)Orchestrated the development and launch of a geospatial big data product built with Spark and a ML model pipeline, generating the first product revenue in 3 months, with a team of 4 Engineers and 3 Product Data Analysts- Data Science Manager, Known GlobalOptimized advertising performance for brands while developing custom pipelines for data ingestion, model training, and batch transformation, building the first company MVP for predictive real-time bidding in programmatic advertising auctions- Director of Science and Product, Floodbase (small startup)Led the ideation, technical development, and launch of two data dashboard products for governments to visualize disaster risk maps based on satellite imagery, growing product revenue 5-fold to >$500,000SKILLS- Programming Languages: Python, SQL, bash, Scala JavaScript, R, Matlab- Tools: Spark, Pandas, Scikit-learn, AWS, SageMaker, LightFM, Streamlit, Google Cloud, Docker- Statistics: Linear/logistic regression, Regularization, Dimensionality Reduction, A/B testing- Machine Learning: CART/XGBoost, LASSO, Ridge, PCA, Collaborative filtering, CNNsEDUCATION- Stanford University 2018PhD, MS, Civil & Environmental EngineeringDeveloped and scaled algorithms for detecting algae using satellite imagery, and used results to understand how climate change affects freshwater resources with machine learning- University of Waterloo 2011BASc, Environmental Engineering
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Senior Product Manager - DataIndeed Apr 2024 - PresentAustin, Texas, Us- Set and executes strategy for measuring who gets hired on Indeed, spearheading novel data collection efforts collectively adding millions of signals for building new models and products- Develop and deploy hire probability models across different surfaces (Search, Recommendations, Bidding, Experimentation)- Lead team of 12 Data Scientists, Engineers, and APMs, setting product vision and sprint priorities -
Product Manager - DataIndeed Jul 2022 - Apr 2024Austin, Texas, Us -
Senior Product Manager - DataSafegraph Jan 2022 - Jul 2022Denver, Colorado, Us- Orchestrated a product plan to develop and launch a new data product targeted toward retailers, investors, and OOH advertisers, growing first $200k annual recurring revenue (ARR) in 3 months- Managed the continued operation and optimization of an existing data product with $5MM ARR, the output of a Learning to Rank algorithm built using Spark in Scala and Python- Performed deep technical analyses in PySpark on quality metrics for guiding optimization roadmap- Set priorities for 3 senior ML engineers by synthesizing business need from go-to-market teams- Directly managed 3 data analysts to inform product decisions, QA pipelines, and build dashboards -
Product Manager - DataSafegraph Apr 2021 - Jan 2022Denver, Colorado, Us -
Senior Data ScientistKnown Nov 2020 - Apr 2021Manhattan, New York, Us- Built an end-to-end machine learning pipeline for collection, training, and deployment to predict real-time bids in programmatic advertising auctions using AWS SageMaker with a custom Docker container - Model pipeline is deployed on a per-client basis and consistently predicts likelihood of conversion with AUC > 0.85 on out-of-sample test data -
Data ScientistKnown Apr 2020 - Oct 2020Manhattan, New York, UsFocusing on clean brands (i.e., good for environment, health and sustainability), I optimized digital advertising spend/performance for clients looking to reach the right audiences efficiently using data-driven approaches. - Reduced cost per site visit for an online direct-to-consumer brand campaign by 50%, and improved customer acquisition cost for another business-to-business performance campaign by 60%- Designed and implemented A/B tests across multiple ad platforms to generate insights about creative, audience, or targeting strategies, and to measure incremental revenue plus brand lift- Automated campaign reporting using SQLAlchemy in Python, reducing weekly time spent by 80% -
Data Science FellowInsight Data Science Jan 2020 - Mar 2020San Francisco, Ca, Us- Helped organic trade associations target advertisements to user segments by predicting likelihood of purchasing organic produce based on past shopping history- Reduced irrelevant ads by 40% by combining product recommendations from collaborative filtering using LightFM with logistic regression with user characteristics using scikit-learn- Visualized purchase likelihoods and recommended products in a web app built using Streamlit and deployed on Amazon EC2 -
Director Of Science And ProductFloodbase Jan 2019 - Dec 2019New York, Us- Led the ideation, technical development, and launch of two disaster analytics data products for government and humanitarian users, growing product revenue 5-fold to >$500,000- Wrote production code in bash for scaling back-end automations using Google Cloud (cron, Pub/Sub) that performed real-time model deployment on satellite imagery in Python- Designed front-end dashboard for delivering insights, guiding front-end developer in Angular- Grew product deployment team from zero to 3 by hiring first three scientists and analysts- Delivered data-driven recommendations that led to the decision for a humanitarian user to relocate 7,000 refugees from a flood-prone area [bit.ly/RefugeeFlooding] -
Senior Remote Sensing ScientistFloodbase Oct 2018 - Dec 2018New York, Us -
Phd ResearcherStanford University Jan 2013 - Aug 2018Stanford, Ca, Us• Created a new three-decade data set of algal bloom occurrence in 76 lakes globally from Landsat using the Google Earth Engine Python and JavaScript APIs, exploring worldwide trends and drivers• Developed a novel method for validating remote sensing algorithms used to identify algal blooms• Presented research findings with six oral presentations and two posters at various academic conferences and at a United Nations Workshop on transboundary water cooperationReceived a 2015 Google Earth Engine Research Award for cutting-edge geospatial analysis based on proposed research.Named a 2014 Rising Environmental Leader Fellow by the Stanford University Woods InstitutePublications: Ho, J.C, A.M. Michalak, and N. Pahlevan. (2019). "Widespread global increase in intense lake phytoplankton blooms since the 1980s." Nature. 574(7780): 667-670.Ho, J.C. and A.M. Michalak. (2019). "Exploring temperature and precipitation impacts on harmful algal blooms across continental US lakes." Limnology and Oceanography. 65(5): 992-1009.Ho, J.C. and A.M. Michalak. (2017). "Phytoplankton blooms in Lake Erie impacted by both long-term and springtime phosphorus loading." Journal of Great Lakes Research. 43(3): 221-227Ho, J.C., R.P. Stumpf, T.B. Bridgeman and A.M. Michalak. (2017). "Using Landsat to extend the historical record of lacustrine phytoplankton blooms: A Lake Erie case study." Remote Sensing of Environment. 191: 273-285Ho, J.C., and A.M. Michalak. (2015). “Challenges in tracking harmful algal blooms: A synthesis of evidence from Lake Erie.” Journal of Great Lakes Research. 41(2), 317-325. -
Ms ResearcherStanford University Sep 2011 - Dec 2012Stanford, Ca, Us• Developed algorithms for monitoring household water access with digitized walking paths from DigitalGlobe satellite imagery in Africa and Central America using Python in ArcGIS • Analyzed multi-dimensional household survey data on rural water use to compare and contrast different metrics for assessing global water accessPublications:Ho, J.C., K.C. Russel and J. Davis. (2014). “The challenge of global water access monitoring: evaluating straight-line distance versus self-reported travel time among rural households in Mozambique” Journal of Water and Health. 12(1), 173-183. -
Undergraduate Research Assistant For Dr. Paul FieguthUniversity Of Waterloo Jan 2011 - Apr 2011Waterloo, Ontario, Ca• Developed algorithms for dust cloud segmentation in time- and space-varying satellite infrared images over Sub-Saharan Africa, using Otsu’s method in Matlab• Compared and evaluated the effectiveness of nine different methods for differentiating cloudpixels from background pixels, mostly based on the rate of change of the infrared signal -
Software Product TesterTrimble Navigation Sep 2009 - Dec 2009Westminster, Co, Us• Developed and executed detailed plans testing integrated GPS technology for environmental problems dealing with mapping and GIS• Conveyed complex product issues succinctly and thoroughly to multi-national development team through the extensive use of oral and written communication• Performed statistical data analyses testing GPS receiver accuracy and reliability• Engaged local universities and businesses in dialog to facilitate educational partnerships
Jeff C. Ho Skills
Jeff C. Ho Education Details
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Stanford UniversityCivil And Environmental Engineering -
Stanford UniversityCivil And Environmental Engineering -
University Of WaterlooHonours Environmental Engineering With Water Resources Option -
National University Of SingaporeEnvironmental Engineering
Frequently Asked Questions about Jeff C. Ho
What company does Jeff C. Ho work for?
Jeff C. Ho works for Indeed
What is Jeff C. Ho's role at the current company?
Jeff C. Ho's current role is Senior Product Manager, Data @ Indeed.
What is Jeff C. Ho's email address?
Jeff C. Ho's email address is je****@****ord.edu
What schools did Jeff C. Ho attend?
Jeff C. Ho attended Stanford University, Stanford University, University Of Waterloo, National University Of Singapore.
What are some of Jeff C. Ho's interests?
Jeff C. Ho has interest in Economic Empowerment, Education, Environment, Poverty Alleviation, Disaster And Humanitarian Relief, Human Rights, Animal Welfare, Health.
What skills is Jeff C. Ho known for?
Jeff C. Ho has skills like Arcgis, Matlab, Simulink, Excel, Monte Carlo Simulation, Data Analysis, Sql, C#, Visual Basic, Groundwater Modeling, Gps, Microsoft Excel.
Who are Jeff C. Ho's colleagues?
Jeff C. Ho's colleagues are Adeline M, Mona Schau, Danny Stacy, Donahue Kennedy, Mario Marsilio, Vlad M., Ryan O'halloran.
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