Experience

Ro

• United States
• Hospitals and Health Care
• 400 - 500 Employee

• Senior Analytics Engineer

  • Aug 2023 - Present

  New York City Metropolitan Area



LinkedIn

• United States
• Software Development
• 700 & Above Employee

• Analytics Engineering Manager

  • Apr 2023 - Aug 2023

  New York, New York, United States Act as a tech lead for an embedded data team. Help stand-up a dbt project for our core data pipeline toolset. Include best practices on how to structure projects, coding standards, and testing requirements. Lead several internal data migration projects. Provide technical feedback to engineering teams on proposed tools for the sales organization to use. Implement RFC process to help team members gain alignment on projects before building.

• Senior Analytics Engineer

  • Sep 2021 - May 2023

  New York, New York, United States Designed and maintained several critical LinkedIn Marketing Solutions (LMS) datasets used across the entire organization. Datasets built using Spark and orchestrated with Azkaban Implemented automated data quality checks on the most frequently used datasets. This helps to proactively flag issues and reduce the time to resolution. Wrote roadmaps for the GTMOPs data foundation team with the goal of introducing engineering rigor into our processes. Mentored team around… Show more Designed and maintained several critical LinkedIn Marketing Solutions (LMS) datasets used across the entire organization. Datasets built using Spark and orchestrated with Azkaban Implemented automated data quality checks on the most frequently used datasets. This helps to proactively flag issues and reduce the time to resolution. Wrote roadmaps for the GTMOPs data foundation team with the goal of introducing engineering rigor into our processes. Mentored team around engineering best practices. Spark and SQL optimization. Implemented code review and CI / CD process.



Nivelo

• United States
• Financial Services
• 1 - 100 Employee

• Machine Learning Engineer

  • Dec 2020 - Jun 2021

  New York City Metropolitan Area As the first full-time ML engineer, I worked build the transaction scoring model to assess risk in ACH payments. Owned model development and optimization.



Daily Harvest

• United States
• Food and Beverage Services
• 100 - 200 Employee

• Machine Learning Engineer

  • Dec 2018 - Dec 2020

  Greater New York City Area Major machine learning projects worked on: Product recommendations model + API -- Lead research in comparing various options for model -- Built Rest API that allows real-time updates to recommendations -- One of the first micro-services project at DH ML Pipeline to estimate lifetime value of customers -- Feature Engineering across all of DH data sources -- Model selection / parameter optimization -- Implemented automated pipeline to build / deploy new… Show more Major machine learning projects worked on: Product recommendations model + API -- Lead research in comparing various options for model -- Built Rest API that allows real-time updates to recommendations -- One of the first micro-services project at DH ML Pipeline to estimate lifetime value of customers -- Feature Engineering across all of DH data sources -- Model selection / parameter optimization -- Implemented automated pipeline to build / deploy new models -- Constant improvements to model to ensure results inline with existing metrics Free text-based search tools -- Built web-toll that allows stakeholders to gain insights from unstructured data -- Implemented via an ElasticSearch cluster -- Combines multiple data source -- Run basic NLP on data Show less



DoubleVerify

• United States
• Advertising Services
• 700 & Above Employee

• Data Scientist

  • Aug 2016 - Dec 2018

  New York, New York -Designed a machine learning pipeline for making daily predictions -- Ran initial data analysis to find features helpful for predicting fraudulent bot ad-traffic --- Dealt with issues including: class imbalance, high dimensional data, feature correlation --Tested a variety of ML algorithms and parameters to find optimal model -Results of several analyses used as supporting data in published industry white papers --Goal was to estimate impact and find websites… Show more -Designed a machine learning pipeline for making daily predictions -- Ran initial data analysis to find features helpful for predicting fraudulent bot ad-traffic --- Dealt with issues including: class imbalance, high dimensional data, feature correlation --Tested a variety of ML algorithms and parameters to find optimal model -Results of several analyses used as supporting data in published industry white papers --Goal was to estimate impact and find websites potentially committing specific type of ad-fraud --Process included clustering techniques, dimensionality reduction, and statistical modeling - Helped create proprietary ad-fraud detection algorithms using statistical and deterministic methods -- Performed initial EDA to identify distinguishing features of proposed fraudulent population --- Ran feature engineering, supervised, and unsupervised learning techniques during data mining --- Focus on having explainable results that can be shared with clients (i.e. avoiding black boxes) -- Validated the ‘quality’ of fraudulent traffic from a statistical and business stand-point --- Summarized and presented findings to COO / Product team for sign-off prior to release --- Revisited impact estimates post-launch to verify accuracy of initial analysis -- Coordinated client-side data collection and algorithm deployment with the fraud development team -- Ability to quickly form plausible hypothesis, validate idea with data, and estimate impact - Created and maintained an R analysis package for internal use within the DV fraud team -- R package maintained in Github for collaboration with remote data scientists

• Senior Fraud Analyst

  • Jan 2016 - Aug 2016

  Greater New York City Area - Helped answer advanced client questions regarding the fraudulent nature of impression traffic - Performed research for Account Management team - Helped AMs create client appropriate messaging - Provided manual vetting of ad-fraud detection algorithms to confirm validity of results - Spent time learning the how and why of ad-fraud before attempting detection techniques



SundaySky

• United States
• Software Development
• 100 - 200 Employee

• Data Analyst

  • Aug 2012 - Jan 2016

  Greater New York City Area Led the Pre-Roll Video Advertising Analytics team, helped create the Campaign Management team, and founding member of Customer Success Engagement analytics team -Performed advanced statistical analysis to determine effectiveness of ads across all business KPIs -Defined A/B tests to validate hypothesis’ on different creative treatments of ads -Identified inefficiencies in ad delivery (internal system bugs, fraud, malware, frequency caps, etc) -Worked with Ad-ops to create… Show more Led the Pre-Roll Video Advertising Analytics team, helped create the Campaign Management team, and founding member of Customer Success Engagement analytics team -Performed advanced statistical analysis to determine effectiveness of ads across all business KPIs -Defined A/B tests to validate hypothesis’ on different creative treatments of ads -Identified inefficiencies in ad delivery (internal system bugs, fraud, malware, frequency caps, etc) -Worked with Ad-ops to create resolution plan to remediate delivery issues and increase value to the client -Created delivery projections / recommendations to increase program scale while maintaining RoAS / CPA -Experienced with advanced multi-touch attribution, traditional last-touch / last-click measurement platforms and incrementality tests (i.e. test vs PSA) -Redefined analytics role in the SmartVideo for Engagement product -Created user engagement best practices to maximize viewership across email/SMS/Portal -Best Practice topics addressed: subject lines, email design, landing page, and survey design -Pre-Launch: Collaborate with client to define business KPI’s that are measurable and ROI positive -Work with customer to verify availability of data sources required for KPI measurement -Forecast video view volume and model customer interaction to verify statistically significant results -Post-Launch: Manage report creation / delivery while monitoring on-going project KPI performance -Run, review, and present ad-hoc reports / analyses to gather insights into project health Show less



Hunter College

• United States
• Higher Education
• 700 & Above Employee

• Adjunct Lecturer

  • Jun 2011 - Aug 2012

  Greater New York City Area Courses Taught: Pre-Calculus (Summer 2011, Fall 20111), Algebra (Fall 2011,Spring 2012), and Everyday Mathematics (Spring 2012) Prepared and presented all lecture material following standardized course syllabus Courses focused on preparing Freshmen/Sophomore students for future mathematics/statistics courses

• Math Tutor

  • Aug 2010 - Sep 2011

  New York, NY Provided one-on-one tutoring for students in Algebra, Pre-Calculus, Calculus (1, 2, and 3), Linear Algebra, Differential Equations, Statistics, and Probability Ran group problem sessions for students in a classroom setting



HLB Lighting Design

• United States
• Architecture and Planning
• 100 - 200 Employee

• Lighting Designer

  • Jun 2005 - Dec 2009

  New York,NY and Los Angeles, CA -Designed, specified, and coordinated architectural lighting designs (electric and daylight) -Worked with architect / contractor to establish and meet overall project lighting budget -Held positions of Lighting Designer, Project Director, DSD Studio Team Leader -Created presentations to communicate proposed lighting solutions to architects and owners -Presentations included summaries of technical calculations, visual renderings of proposed designs, and existing photographs of… Show more -Designed, specified, and coordinated architectural lighting designs (electric and daylight) -Worked with architect / contractor to establish and meet overall project lighting budget -Held positions of Lighting Designer, Project Director, DSD Studio Team Leader -Created presentations to communicate proposed lighting solutions to architects and owners -Presentations included summaries of technical calculations, visual renderings of proposed designs, and existing photographs of similar existing projects to convey overall concepts -Reviewed and redesigned standard documents and procedures to increase overall office effectiveness and efficiencies -Examples include: created standard Excel calculation files and calculation result summary sheets -Concurrently worked on and independently managed deadlines for multiple projects -Coordinated with architect/engineer to establish and meet project deadlines and goals -Founding team member of the HLB “Daylight and Sustainable Design Studio” Show less



University of Colorado Boulder

• United States
• Higher Education
• 700 & Above Employee

• Teaching assistant

  • Jan 2005 - May 2005

  teaching assistant for CAD drafting class



Flatiron Surveying

• draftsman

  • May 2001 - May 2005

  CAD draftsman and land surveyor