Marco Alban-Hidalgo
About
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Co-Founder & CTO
New York, United States
Résumé
Jobs
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Co-Founder & CTOAtomic InvestAug 2020 - Current (5 years 11 months)- Senior Machine Learning Product ManagerUiPathAug 2020
- Machine Learning Product ManagerUiPathAug 2019 - Aug 2020 (1 year 1 month)Product Manager for AI Center (AI/ML platform for delivery and continuous retraining).
- Product ManagervmwareJan 2018 - Dec 2018 (1 year)• Increased conversion of customer onboarding by mapping customer lifecycle, defining and aligning team on success metrics, working cross-functionally to set up systems to measure and analyze product performance. • Launched new onboard flow by proposing mockups, initiatives and working with UX and engineering to drive implementation. • Aligned cross-functional team toward key retention behaviors by setting up report (leveraging technical skills to build data pipeline and write complex SQL queries), gathering and synthetizing customer surveys and prioritizing new features. • Product outcomes repeated across product line; framework was so successful that by the end of tenure, manager’s manager championed adoption across multiple products.
- Product GTMSumUpJan 2018 - Dec 2018 (1 year)• Markedly reduced product operations expenses; set milestone roadmap, prioritization, and optimal partner choice of product operations backed by financial model and industry benchmark, performance recognized by c-suite. • Directly increased bottom line by more than .1% (est. greater than 150K/quarter) by building a system to solve a constrained convex-optimization problem to determine optimal partners on a per transaction level.
- Associate Fellowship (Venture Capital)Radicle Impact PartnersJan 2018 - Dec 2018 (1 year)• Enabled new perspectives and decision-criteria by building blockchain investment thesis and primer.
- Software EngineerThoughtSpotJun 2016 - Aug 2017 (1 year 3 months)• Launched new product in two person team; led backend development and collaborated in product management (ideation, roadmap, milestones, tracking success), work recognized at all-hands by the CEO and received a non-scheduled performance bonus. • Shipped previously unatainnable value to customers by proposing, designing, and implementing a user experience for answering geo-spatial queries; immediately opening up new prospects including a Fortune 50. • Delivered on company’s goal to be at the forefront of technology by building a Natural Language Understanding engine for interactive question answering. Chosen to be part of this high-visible, highly critical initiative working with 1 other engineer and directly with CTO and advisor (Ex-VP at
- Machine Learning EngineerSidewireJan 2015 - Dec 2015 (1 year)• Gave internal Editor Team almost a fifth of their day back by creating a data pipeline and machine learning system that automated a manual process in their workflow, performing better than a third-party solution commercializing that service. • Released markedly better user experience by refactoring backend to be multi-threaded backend.
- Research And Development EngineeraccentureJan 2014 - Dec 2014 (1 year)• Unlocked the business potential of an in-house system by enabling clients to get results an order of magnitude faster. Formulated a graph sampling algorithm inducing a more than 70% reduction in platform’s input size, recognized by US patent 20170324759.
- Hardware EngineerArista NetworksJan 2013 - Dec 2013 (1 year)
Education
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- Master of Business Administration - MBAStanford University Graduate School of BusinessAmong other courses, activities, and societies, I was part of the highly selective Lean Launchpad cohort taught by Steve Blank.
- Bachelor's degree, Electrical and Electronics Engineering, Electrical and Electronics EngineeringStanford UniversitySignal Processing
- Master's degree, Computer Science (Artificial Intelligence, Computer Science (Artificial Intelligence)Stanford UniversityTeacher Assistant CS 229 Machine Learning - Andrew Ng (Fall), John Duchi (Spring) I loved my time teaching and mentoring students. At Stanford I lectured classes of 300+ students, held office hours, graded papers and exams, and evaluated countless machine learning projects . More than a few times I was stopped at Stanford's Coupa Cafe or at the gym by students telling me that my lecture was one of the most clear and helpful. I was selected to TA this course both times it was taught due to my distinguished performance. Teacher Assistant CS 228 Probabilistic Graphical Models - Stefano Ermon My office hours were routinely over-subscribed; one of my biggest sources of meaning during my time at Stanford was reading my students' reviews and lea
Publications
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- aLow Latency Anomaly Detection and Bayesian Network Prediction of Anomaly LikelihoodarXivNov 2016We develop a supervised machine learning model that detects anomalies in systems in real time. Our model processes unbounded streams of data into time series which then form the basis of a low-latency anomaly detection model. Moreover, we extend our preliminary goal of just anomaly detection to simultaneous anomaly prediction. We approach this very challenging problem by developing a Bayesian Network framework that captures the information about the parameters of the lagged regressors calibrated in the first part of our approach and use this structure to learn local conditional probability distributions.