Johannes Bauer

Data Science Executive Director at S&P Global

Greater London, England, United Kingdom

About

• Experienced data science professional • Strongly committed to driving business value for machine learning application • Profound experience in statistics, machine learning techniques and big data analytics • Strong research background (30+ publications, 1000+ citations and 50+ invited talks, https://scholar.google.com/citations?hl=en&user=iU77ObYAAAAJ&view_op=list_works) • Passionate about finding solutions for the future of energy (http://www.energydatascience.co.uk/)

Experience

  • Data Science Executive Director at S&P Global at S&P Global
    Mar 2022 - Present · 4 yrs 4 mos

  • IHS Markit (5 yrs 1 mo)
    • Data Analytics Executive Director
      Mar 2020 - Apr 2022 · 2 yrs 2 mos

      Leading multiple data science initiatives across the company. Working with business stakeholders and team of data scientists on predictive modeling for products in financial services, transportation, and energy

    • Data Analytics Director
      Feb 2019 - Mar 2020 · 1 yr 2 mos

      Analytics and predictive modeling related to financial products/services, transportation, and energy

    • Data Scientist
      Apr 2017 - Jan 2019 · 1 yr 10 mos

      Both hands-on work and technical leadership on projects (Proof of Concept to Production) on e.g., Investment factors, portfolio optimization, index generation, advanced data imputation techniques, price predictions, forecasting.

  • Data Scientist, Lead Data Engineer at SCL Group
    Sep 2015 - Mar 2017 · 1 yr 7 mos

    • Work on data pipelines and development of client and inhouse ML models • In charge of data engineering team, ETL and database management work; technology stack AWS, MySQL, python, scala, git.

  • Data Scientist at The ASI
    Jul 2015 - Aug 2015 · 2 mos

    • Training on Data Science concepts and technologies • Re-engineering prediction model with Spark MLLib

  • Researcher at Harvard University
    May 2012 - Aug 2015 · 3 yrs 4 mos

    • Research in theoretical condensed matter physics on superconductivity and magnetism • Analysis of quantum many-body systems with large scale simulation and parallel computation • Handling large, multi-dimensional data sets