David Mcgarry Email and Phone Number
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I am an engineering leader with over 15 years of experience in machine learning, data science, and data engineering. Over my career I have worn many hats and am equally comfortable managing teams as I am leading as a senior individual contributor. My true passion is mentorship and nothing fulfills me more than helping machine learning engineers, data scientists and data engineers grow. I am currently contracting and offering services that include:• Training, deploying and monitoring ML models at scale (batch & real-time inference).• Building scalable data pipelines (data ingests, feature engineering, etc...).• LLM/GenAI integration.• Backend application development.• Feature experimentation and measurement (A/B tests, backtesting, attribution, etc...).• Defining data/ML/AI visions and roadmaps.• Technical architecture design and implementation.• People management, coaching and mentorship.• Translating business problems into data products & engineering solutions.• Defining and rolling out metrics-based goals, KPIs and strategic plans.My contract workload is quite full for the foreseeable future, but feel free to reach out with smaller opportunities as I may be able to squeeze in short-term engagements and/or up to 8 hours per week on a longer-term basis. Regarding salaried roles: I'm generally not interested at the moment but am willing to explore opportunities that could be the "perfect fit", which would require at least the following to be true: the organization has a socially responsible mission, there is a strong people-first culture that aligns with core values including integrity, transparency and humility, and there is the potential for a 4 day work-week.
Self Employed
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Freelance Machine Learning Leader And EngineerSelf EmployedLouisville, Co, Us -
Freelance Machine Learning Leader/EngineerSelf Employed Feb 2021 - PresentSatellite Beach, Florida, UsHomebound | Machine Learning Engineer (July 2021 - Present)• Leading Homebound's machine learning and pricing applications teams.Gitcoin | Data Science Technical Assessment (July 2023 - September 2023)• Conducted technical interviews and made hiring recommendations for Gitcoin's first two data scientist hires.Justice Reskill | Chief Technology Officer (February 2021 - June 2021)• Acted as the Interim CTO for Justice Reskill, an early stage non-profit startup that seeks to advocate for, support, and train justice involved individuals with a focus on landing them jobs in tech.• Played an integral role in forming the organization’s culture, engineering processes, and strategic technical plan.• Developed the engineering department’s career pathing, hiring strategy, and interview playbooks. -
Machine Learning EngineerDatarobot Aug 2019 - May 2021Boston, Massachusetts, Us• Researched, tested and implemented optimizations to the default settings of DataRobot’s AutoML algorithm, resulting in a ~15% reduction to cloud costs and wall-time at the cost of only a ~0.25% decrease in accuracy.• Led the project and acted as the lead engineer for development of DataRobot’s unsupervised clustering product suite.• Developed a highly efficient AutoML mode that trained models at half the cost and time with only a ~3% impact to accuracy.• Built an AutoML mode that maximized accuracy for users who valued model accuracy over training time and cost.• Managed the hiring funnel for MLEs, including: screening resumes, reviewing technical tests, and conducting interviews. -
Director/Head Of Data & Machine LearningGaia Inc. May 2018 - Aug 2019Louisville, Co, Us• Architected and led the technical migration from an unstable and cost-prohibitive data warehouse to a horizontally scalable Data Lake.• Trained and implemented a recommendation system that resulted in a 90% lift in minutes of content watched over the existing collaborative filtering approach.• Hired, managed, and built the data science and data engineering teams.• Designed the multivariate testing and experimentation process that is used to evaluate the impact of all new product features.• Built automated CI/CD processes that enabled data engineering and data science to seamlessly release python packages and data products into production. -
Director/Head Of Data & Machine LearningIbotta, Inc. Jan 2017 - May 2018Denver, Colorado, Us• Built, hired, mentored, and led a 23 person department of machine learning, data engineering, and data science teams.• Defined the strategic vision for Ibotta’s Data, including: data infrastructure, internal data products, and data monetization opportunities.• Oversaw the creation and production deployment of multiple business impacting ML products, including Ibotta's: personalized recommendation engine, audience targeting product suite, and internal A/B testing platform.• Pioneered the migration from a data warehouse to a S3 data lake that leverages distributed big data tools like Spark, Hive, and Presto.• Designed and built a recommender system that resulted in an incremental ~4M in annual revenue over the existing collaborative filtering based algorithm. -
Director Of Data ScienceOracle Jul 2016 - Jan 2017Austin, Texas, Us• Launched, hired, and managed two R&D data science teams, one full-stack team that built SaaS and DaaS products, and another that developed internal machine learning data products.• Spearheaded the career development and mentorship initiative within the Data Science department. -
Principal Data ScientistOracle Nov 2015 - Jul 2016Austin, Texas, Us• Redesigned the methodology and predictive data features for the ODC’s high revenue product, resulting in a 100% lift in accuracy and 300% improvement to computation costs.• Developed machine learning models that determine a household's propensity to purchase close to 200 different categorizations of CPG products.• Built machine learning models that determine a household's likelihood to experience 9 different life events in the near future.• Built an efficient machine learning system using Spark and Python that improved the daily assignment of demographics for 1.5 billion cookies by 200-500%. -
Director/Head Of Data ScienceReturn Path Jul 2015 - Nov 2015Boston, Massachusetts, Us• Defined the strategic vision for the four teams within Return Path’s Data Science and Analytics department. • Drove the strategy for Return Path’s Data Organization by working alongside senior leaders in engineering, product management and marketing as a core member of the Data Senior Leadership Team. • Oversaw, managed and mentored 15 data scientists, statisticians and data analysts spread across the four teams in the department. • Provided the context and framework for the teams within the Data Science and Analytics department to deliver on business-outcome oriented goals. -
Manager Of Data ScienceReturn Path Jan 2015 - Jul 2015Boston, Massachusetts, Us• Defined and launched Return Path’s Feature Engineering team, which became a role model in the organization within its first quarter. • Managed, mentored and hired a team of data scientists that focused on the efficient development of scalable machine learning models. • Leveraged data from trillions of emails to build machine learning driven business solutions as Return Path’s lead data scientist. • Collaborated with Data Engineering to develop a process using Kafka, Storm and Thrift to deploy machine learning models that consume hundreds of millions of raw emails a day in real-time. • Routinely gathered, interpreted and scoped stakeholder requirements, developed the department’s first year-long rolling roadmap and participated in the Data Team’s quarterly agile planning as the acting product manager for the Feature Engineering team. • Led the department initiative to define measurable team-based KPIs and surface them to senior leaders in the company via dashboards. -
Data ScientistReturn Path Apr 2014 - Jan 2015Boston, Massachusetts, Us• Led the technical components of a R&D project by working closely with clients and Executive team members to define and develop the Return Path’s first data-as-a-service product and third line of business, Consumer Insights. • Built a machine learning classification model with Python that efficiently categorizes hundreds of millions of purchased products into 50+ categories.• Created a PII redaction and re-identification risk process for a monthly data feed of tens of millions of rows. • Devolved prototypes of consumer loyalty metrics using unsupervised learning methods as part of a R&D project.• Designed and implemented an improved new hire on-boarding system and department wide career development program.• Mentored and trained a team of aspiring data scientists and statisticians. -
Data AnalystReturn Path Jan 2013 - Apr 2014Boston, Massachusetts, Us• Developed a collection of predictive models in Python that efficiently classify the content of millions of email messages every day.• Created and automated the daily assignment of mailbox type categorizations to millions of email addresses using unsupervised clustering algorithms in R.• Built a predictive model and accompanying report that identifies our clients’ churn risk.• Designed and built multiple interactive data analysis web applications that have enabled internal staff to quickly and easily make better informed decisions.• Founded a predictive modeling challenge that teaches practical data science to staff across the company and provides crowdsourced solutions to valuable business problems.• Developed and taught weekly instructional sessions for colleagues on topics including: efficient programming in R and Python, machine learning, statistical analysis and project management. -
Senior Data Services SpecialistNew York University Feb 2012 - Jan 2013New York, Ny, Us• Managed all quantitative research services at NYU’s Data Services, including a team of 2.5 full-time staff members and 7 graduate student consultants.• Provided statistical computing assistance to faculty, staff and student researchers as the Data Service’s lead quantitative programming consultant.• Designed lessons, wrote training documentation and taught classes for statistical computing tools, including: R, High Performance Computing, SQL, SAS and SPSS.• Conceptualized, recommended and implemented integral revisions to the Data Service’s service model, including the support of High Performance Computing, SQL and Python.• Designed methods for the collection, analysis and reporting of internal usage metrics for the Data Services and High Performance Computing Clusters. -
Data Services SpecialistNew York University Jan 2009 - Feb 2012New York, Ny, Us
David Mcgarry Skills
David Mcgarry Education Details
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New York UniversityInformation Systems -
Hunter CollegeStatistics
Frequently Asked Questions about David Mcgarry
What company does David Mcgarry work for?
David Mcgarry works for Self Employed
What is David Mcgarry's role at the current company?
David Mcgarry's current role is Freelance Machine Learning Leader and Engineer.
What is David Mcgarry's email address?
David Mcgarry's email address is da****@****cle.com
What is David Mcgarry's direct phone number?
David Mcgarry's direct phone number is +160336*****
What schools did David Mcgarry attend?
David Mcgarry attended New York University, Hunter College.
What skills is David Mcgarry known for?
David Mcgarry has skills like Machine Learning, Python, Team Leadership, Mentoring, Natural Language Processing, Apache Spark, Hive, Predictive Modeling, Unsupervised Learning, R, Statistics, Data Mining.
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