Data Scientist

Meridiam is an independent investment Benefit Corporation and asset manager, established in 2005 by Thierry Déau. Our company focuses on the development, financing, and long-term management of sustainable public infrastructure in three main sectors: sustainable mobility, critical public services, and innovative low carbon solutions.

Job Overview:

The role of Data Scientist will allow you the opportunity to use your data-driven skills to optimize our operation of our portfolio company performance as well as supporting the development of new project opportunities. You will work with industry leaders both internally and externally to use advanced analytics to understand and optimize revenue projections and pricing strategies for demand-risk projects across multiple sectors – specifically including transportation (highways and airports), digital and energy.

Key Responsibilities:

• Integrated Team Member:
  • Work with the Asset Management and Project Development teams for direct application in operations and pursuits in demand risk projects.
• Management:
  • Specification and management of the data analytics tools necessary to support the data analysis needs.
  • In conjunction with the IT department, management of external consultants and any analytics out-sourcing.
• Portfolio Data analysis:
  • Applying analytics tools (including AI) to find trends, patterns in existing project data sets.
  • Utilizing trends to support price and demand optimization on existing projects.
  • Support the development of forecasts for existing projects.
• Project Development:
  • Support the demand and revenue workstreams of new project development and portfolio management teams.
• Innovation:
  • Identify projects or sectors which may benefit from advanced analytics.
  • Identify, develop and implement analytics projects which may benefit Meridiam, its projects or potential opportunities.
  • Be current on industry trends, developments and participants in the data analysis sector relevant to our work.

Qualifications:

• Master’s degree in a quantitative field such as Operations Research, Data Science, Statistics, Civil or Industrial Engineering.
• Proficiency in advanced analytic techniques.
• High level of skill in relevant analytics software packages and language
• Ability to present visualizations of data findings using software tools