Clay Violand

Data Scientist & Weinberater

Mainz, Rhineland-Palatinate, Germany

About

Data Scientist holding MSc and eights years professional experience with additional achievements in academics and research. Skilled in data processing and analytics, machine learning, predictive modeling, computer vision, programming and git collaboration. Seeking to improve product and inform business decisions through evidence-based methods and programmatic means. Also a trained winemaker and WSET3 holder, freelancing as Violand Weinberatung for the wine sector in Germany in both a technological and general consulting capacity.

Experience

  • Weinberater at Violand Weinberatung
    Dec 2021 - Present · 4 yrs 7 mos

  • Senior Data Scientist at Access to Energy Institute
    Nov 2019 - Present · 6 yrs 8 mos

  • Senior Data Scientist at SoundCloud
    Dec 2018 - Aug 2019 · 9 mos

    As part of the Strategy & Analytics team, I focus on informing company strategy through in-depth understanding of user behaviour and product/content dynamics. I generate strategic value from SoundCloud's vast data asset and am responsible for conducting behavioural analyses, designing, running and interpreting experiments, creating analytical frameworks, designing dashboards and building predictive models in an effort to inform decision making. Some core tech includes: SQL, Python, AWS, GCP (e.g. BigQuery, Data Studio, Datalab), Airflow, Docker, Hadoop, Braze.

  • Data Scientist at Mobisol Group
    Apr 2015 - Nov 2018 · 3 yrs 8 mos

    The purpose of the Data Science department is both practical and exploratory, existing to answer to the needs of other departments’ data-based inquiries or projects through computer programming, and to explore and discover new ways of adding additional benefit to the company by analyzing available data through programmatic means. The responsibilities of the Data Scientist are to provide and maintain data analyses for any requesting department, as well as to design, implement and maintain advanced data-processing/data-analyses systems using both traditional statistics as well as machine learning/artificial intelligence methods. Often, the Data Science department will serve as a means of accomplishing a goal through a “big-data” based approach that would otherwise not be possible through qualitative or non-programmatic means.

  • The Graduate Center, City University of New York (Greater New York City Area)
    • IT Support Technician
      Aug 2013 - May 2014 · 10 mos

      Worked alongside graduate studies as an IT professional at The Graduate Center Library Help Desk.

    • Graduate Research Assistant
      Aug 2013 - May 2014 · 10 mos

      Worked alongside graduate studies at the Second Language Acquisition Lab processing language-learning data for the creation of two semi-adaptive literacy assessments in multiple languages for the New York City Department of Education and New York State Education Department.