Senior Research Engineer — Private Assets

Senior Research Engineer — Private Assets

Location: Singapore or London
Organisation: EDHEC Infrastructure & Private Assets (EIPA)
Contract: Full-time
Seniority: Experienced hire

About EIPA

The EDHEC Infrastructure & Private Assets Research Institute is an applied research centre focused on improving the way private assets are measured, valued and understood by institutional investors, regulators and market participants.

Our work challenges flawed practices in private asset investing and develops more scientific, transparent and robust approaches to valuation, risk measurement, performance attribution and alpha measurement. Current research priorities include private asset valuation accuracy, fair value practices, private equity volatility, private debt risk, factor models for infrastructure and private equity and alpha measurement.

We are looking to recruit Senior Research Engineers to strengthen our research capacity and turn ambitious private-assets research ideas into rigorous empirical outputs, working papers, academic journal submissions and practitioner-facing publications.

The role

The Senior Research Engineer will work at the intersection of private assets, empirical finance, quantitative methods, data engineering and academic research.

The successful candidate will build and analyse datasets across private equity, infrastructure, private debt and related alternative asset classes. They will take ownership of empirical work on topics such as valuation accuracy, private asset volatility, performance attribution, factor exposures, GP behaviour, private-market alpha and risk estimation.

Key responsibilities

The Senior Research Engineer will:

• Work with EIPA researchers to design, implement and test empirical research methods in private assets. 

• Build and maintain research datasets using sources such as company accounts, transaction databases, regulatory filings, fund disclosures, valuation records and commercial private-market databases. 

• Lead and execute empirical analysis for working papers, policy papers, insight papers and academic journal submissions.

• Translate research questions into robust empirical designs, including regression analysis, panel data methods, difference-in-differences, factor models, event studies, network analysis and other quantitative techniques. 

• Develop research on private asset valuation accuracy, fair value practices, volatility estimation, alpha measurement, private equity value creation, private debt risk and infrastructure expected returns.

• Develop reproducible research code, data pipelines and documentation that allow results to be audited, replicated and extended. 

• Prepare publication-quality tables, figures, robustness checks and methodological appendices for academic papers.

• Identify data limitations, measurement problems and methodological weaknesses in existing private-market research.

• Draft sections of research papers, especially methodology, data, empirical results and robustness sections.

• Drive publication efforts in academic and practitioner outlets, including responding to referee comments and revising empirical analysis where required.

• Collaborate with internal teams and external academic or industry partners where appropriate. 

• Mentor junior researchers, analysts or research assistants on coding, data quality and empirical methods. 

Current research areas

The role will advance EIPA’s research pipeline across three broad areas.

Valuation and transparency

This includes work on the accuracy of private asset valuations, fair value practices, ASC 820 / IFRS 13 Level 3 disclosures, valuation policy, valuation backtesting, listed private equity fund holdings, BDC mark accuracy and the incorporation of climate risks into infrastructure valuations.

Risk measurement

This includes work on private asset volatility, private debt spreads, BDC loan concentration, network analysis of private asset markets, total portfolio risk management and improved estimation of systematic risk in infrastructure and private equity.

Alpha and performance measurement

This includes research on private-market alpha, return attribution, secondary buyouts, GP de-risking and factor timing, private equity value creation, mimicking finance for private assets and the construction of large-scale private equity datasets.

Required experience

Candidates should have:

• Strong exposure to private assets, alternative investments or institutional investment research.

• Strong ability to work with researchers and quantitative methods. 

• Demonstrated experience conducting empirical research, ideally in finance, economics, accounting, investment management or a related field. 

• The ability to produce research that can be submitted to academic journals, including familiarity with empirical research standards, robustness testing, literature positioning and academic writing.

• Advanced programming ability, preferably in Python and/or R. 

• Strong data skills, including experience with messy, incomplete and multi-source datasets. 

• Good knowledge of econometrics, statistics or quantitative finance. 

• Experience with SQL or structured databases. 

• Strong understanding of reproducible research practices, including version control, documentation, code review and testing. 

• Ability to explain technical methods and empirical results clearly to both academic and non-technical audiences. 

• Excellent written English and the ability to write directly for research papers.

Desirable experience

The following would be particularly valuable:

• Familiarity with the literature in private assets, alternative investments or institutional investment, including private equity, infrastructure, private debt, real estate, private credit, project finance, asset management, pension funds, sovereign wealth funds, investment consulting or private-market data providers.

• A PhD or research master’s degree in finance, economics, accounting, statistics, data science, engineering, mathematics or a related discipline. 

• Previous publication record in academic journals, working papers, SSRN papers or high-quality applied research. 

• Experience with private equity datasets such as Orbis, PitchBook, Preqin, Capital IQ, Burgiss, EDGAR filings or fund-level datasets. 

• Experience with valuation research, fair value accounting, Level 3 assets, ASC 820, IFRS 13 or private-market NAV reporting. 

• Experience with asset pricing, factor models, return attribution, volatility estimation or total portfolio risk models. 

• Experience with panel data, causal inference, difference-in-differences, event studies, machine learning, network analysis or NLP. 

• Knowledge of infrastructure finance, regulated utilities, private debt or BDCs. 

• Experience collaborating with academic co-authors or responding to journal referee reports. 

• Experience producing both academic papers and practitioner-facing research.

Candidate profile

We are looking for someone who is intellectually rigorous, empirically minded and comfortable working on difficult private-market problems where the data are imperfect and the methodology matters.

The ideal candidate will be able to move between code, data, financial theory and research writing. They should be comfortable asking whether a result is economically meaningful, whether a model is correctly specified, whether a dataset is biased, and whether the evidence is strong enough for publication.

This role would suit a research engineer, empirical finance researcher, quantitative analyst, data scientist or applied economist who wants to work on high-impact private-assets research with both academic and industry relevance.

Technical skills

The ideal candidate will have strong skills in several of the following:

• Python and/or R 

• SQL 

• Git / GitHub 

• Econometric and statistical modelling 

• Panel data methods 

• Data cleaning and entity resolution 

• Financial statement data 

• Regulatory filings and disclosure data 

• Private-market transaction and fund data 

• Reproducible research workflows  

• Research documentation and methodological appendices 

Knowledge of graph databases, network analysis, machine learning, cloud platforms or large-scale data pipelines would be helpful but is not essential.

Why join EIPA?

This is an opportunity to work on some of the most important unresolved questions in private markets: how private assets should be valued, how risky they really are, whether managers generate genuine alpha, and how institutional investors should measure performance and allocate capital.

The role offers the chance to produce research that is academically credible, practically relevant and directly connected to major debates in private asset investing.

Application

Applicants should submit a CV and a short cover letter explaining:

• Their experience in private assets or alternative investments. 

• Their experience with empirical research and quantitative methods. 

• Their programming and data skills. 

• Their publication experience or ability to write for academic journal submissions.

Please note: Only shortlisted candidates will be contacted. If you do not hear from us within 21 days, please assume your application has not been successful on this occasion.