ERM is seeking a (Senior) Quantitative Researcher to develop algorithms, financial models, and analytical tools that link non-financial ESG data with financial outcomes. This role is ideal for a professional with a strong quantitative background, proficient in statistical modelling, machine learning, and financial analysis. The candidate will work on transforming sustainability materiality and maturity frameworks into automated, scalable models that assess performance and valuation impacts.
This is a non-client-facing offshore role focused on data-driven ESG research and tool development.
The Ideal Candidate
You bring a robust background in financial modelling and valuation with a deep passion for sustainability (e.g. climate, nature, employees wellbeing, sustainable revenue). You have demonstrated success in integrating ESG factors into transaction analysis and investment decision-making. With experience in investment banking, strategy consulting, or transaction advisory—and preferably exposure to private equity—you are adept at turning complex and qualitative ESG concepts into actionable financial insights. You will be able to communicate with senior stakeholders and provide thought leader in this evolving space.
RESPONSIBILITIES:
Quantitative Research & Algorithm Development
- Design data-driven models that quantify the impact of ESG factors on financial performance.
- Develop statistical algorithms that integrate materiality and maturity definitions into predictive financial models.
- Leverage machine learning techniques (e.g., regression analysis, clustering, time-series forecasting) to identify trends in ESG data.
Data Analysis & Model Development
- Build automated financial modelling tools that incorporate non-financial (ESG) data and financial metrics.
- Develop custom ESG performance indicators that can be used in due diligence, exit readiness, and investment decision-making.
- Standardize ESG data inputs and apply weightings/scoring methodologies to determine financial relevance.
Tool Development & Automation
- Work with developers to code ESG models into dashboards or automated financial tools.
- Implement AI/ML techniques to enhance model predictive capabilities.
- Ensure models are scalable and adaptable across multiple industries and investment types.
Data Management & Validation
- Collect, clean, and structure large datasets from financial reports, ESG databases, and regulatory filings.
- Conduct sensitivity analyses to validate model accuracy and effectiveness.
- Ensure consistency in ESG metrics and definitions across all analytical frameworks.
REQUIRED SKILLS & EXPERIENCE:
Educational Background
- Master’s in Finance, Econometrics, Data Science, Quantitative Economics, Mathematics, Statistics, or a related field.
- CFA, FRM, or other financial analysis certifications are a plus.
Technical & Analytical Proficiency
- Financial & Statistical Modelling: Advanced Excel, Python, R, or MATLAB for quantitative research and financial modelling.
- Machine Learning & AI: Proficiency in ML algorithms for forecasting, clustering, and risk modelling.
- Data Analysis & Automation: Experience with SQL, Power BI, or other data visualization tools.
- ESG & Financial Integration: Understanding of ESG materiality frameworks (SASB, MSCI, S&P, etc.) and their impact on valuations.
Professional Experience
- Minimum 5-8 years in quantitative research, financial modelling, or ESG data analysis.
- Experience in building proprietary financial tools/models for investment firms or financial consultancies.
- Strong background in factor modelling, risk assessment, and alternative data analysis.
Personal Attributes
- Highly analytical, structured thinker with attention to detail.
- Ability to work independently in an offshore role, managing multiple datasets and models.
- Passion for quantifying ESG impact in financial terms.
