Manager - Lead Economist - Carbon Markets Analytics & Forecasts

Purpose of the position

The person would help clients build a better understanding of carbon markets by developing visualization driven insights, and by enhancing / developing models on several carbon offset markets. These would include Cap and Trade markets, Clean Fuels Markets across North America, Global Voluntary Carbon markets, etc.

Key responsibilities :

The role envisages the following activities:

- Maintaining and adding data-pipes on information that impact carbon markets

- Updating existing econometric/ data models and developing new relevant models pertaining to Carbon allowances, offsets, LCFS etc.

- Develop forward looking projections and views on issues pertaining to carbon markets. Analyzing a variety of data streams using mathematical models and statistical techniques

- Supporting delivery of reports and analysis - working with teams across the firm that require data/ insights

- Managing / mentoring a small team of data scientists and data engineers

- Understanding how clients are using the data/ models and finding ways of improving the client experience

- Supporting and actively participate in product development and management

Candidate Requirements :

The ideal candidate must :

- Have been working with analysing data already and looking to operate in carbon markets

- Have a methodical and curious mindset

- Be comfortable being an individual contributor as well as can manage a small team

- Be familiar with basics of data preparation and a variety of approaches to use data to solve problems
(econometric tools, machine learning, linear programming and the likes)

- Be experienced in climate policy, energy markets and/or environmental commodity markets is a big
plus

- Have demonstrated knowledge and use of standard analytical software such Python, Microsoft excel,
R, or SPSS

Job Description :

- Be passionate for creating newer products and experience having done so

- Have ability to work 'hands-on'

Academic qualifications & Experience :

- Post-graduation in a relevant discipline such as economics, financial engineering, data science, statistics, applied mathematics, etc.

- 7+ years of work experience, including 5+ years in building models or recommendation solutions