Mark W. Email & Phone Number

Missoula, Mt, Us

Durham, New Hampshire, Us

- Spearheaded the launch of our Spatial Exploration and Plan features, as well as improvements in our data processing pipelines.

Durham, New Hampshire, Us

- Optimized our python- and PostgreSQL-backed pipeline for processing agricultural data across North America.– Used domain-driven design principles to productionize our data models, allowing us to scale to more customers and geographic locales.

San Francisco, California, Us

- Responsible for the technical execution and success of a team of 7 full-stack engineers.

San Francisco, California, Us

- Led and launched projects for automatic goal progress updates, time periods support, improved goal loading, and goal drag and drop features.– As project lead, acted as engineering partner to our product manager in defining the feature requirements, designed and prototyped the technical approach, organized risk analysis workshops, broke down and assigned work, reviewed team member design docs, contributed to implementation, and shared bi-weekly updates with stakeholders.

Mountain View, Ca, Us

– Full-stack engineer on Google Slides, building user-facing features from early stage prototyping, product development, data model changes, through implementation, launch, and quality monitoring.– Backend engineer on an internal ticketing tool called SupportPlus, creating the the data validation and storage layer for a RESTful API.– Participated in internal training programs for Site Reliability Engineering and TensorFlow basics.

Verona, Wi, Us

Developed enhancements for Hospital Emergency Departments, focusing on tools for nurses to efficiently record patient data in a variety of urgent situations.

Princeton, Nj, Us

Explained basic principles of computer science and aided in teaching coding and debugging techniques to Princeton undergraduates enrolled in introductory computer science courses.

Bangalore, Karnataka, In

Researched and presented on the use of Hadoop and Mahout to analyze large security data sets. Developed methods in Java and Python for clustering security logs to optimize research and product development.