Patrick Gerbes

Patrick Gerbes is a highly motivated individual who excels in tackling complex, undefined problems that require a blend of creativity, mathematics, software engineering, and innovative thinking.

His research interests and expertise span across various domains including unsupervised learning, supervised learning, operations research, econometrics, and computer vision.

Patrick is proficient in a range of technologies including Scala, R, Haskell, SQL, JavaScript, as well as data processing tools such as Spark, Redshift, Kinesis, S3, PostgreSQL, and MongoDB.

He is experienced in utilizing frameworks like Play, Lift, Grails, and Node.js, and deployment tools like EC2, Elastic Beanstalk, sbt, and gradle.

Patrick Gerbes has a background in Economics and Mathematics from Boston University and has held key data science positions in renowned companies like SuperRare Labs, Storj, Experience LLC, Decision Street, and Clayton Holdings LLC.

He is also active on GitHub, showcasing his project contributions and collaborations.

His professional journey includes roles ranging from Principal Data Scientist to Operations Analyst, exhibiting his diversely skilled background in data analytics and operations.

Patrick's drive lies in leveraging technology to create impactful solutions that have the potential to make a difference globally.