"Research Fellow (Contract appointment ending 31 August 2026), SKBI"

Research Fellow (Contract appointment ending 31 August 2026), SKBI

• Operation
• Contract
• Employment Type
• Manager
• Experience Level
• Master's or equivalent | Doctorate or equivalent
• Education Level
• Singapore | Closing On 07 Mar 2026
• Country
• Hybrid
• Working Arrangement

About Us

Singapore Management University is a place where high-level professionalism blends together with a healthy informality. The 'family-like' atmosphere among the SMU community fosters a culture where employees work, plan, organise and play together - building a strong collegiality and morale within the university.

Our commitment to attract and retain talent is ongoing. We offer attractive benefits and welfare, competitive compensation packages, and generous professional development opportunities - all to meet the work-life needs of our staff. No wonder, then, that SMU continues to be given numerous awards and recognition for its human resource excellence.

Job Description

• This position is for Sim Kee Boon Institute for Financial Economics (SKBI).
• Quantitative Framework Design & Index Construction:
• Translate qualitative theoretical factors into measurable quantitative metrics or factors.
• Develop a data-driven scoring and weighting methodology (e.g. weighted averages, conditional logit or other limited dependent variable models, Bayesian models, Hierarchical models etc.) to measure the "Readiness Level" of a specific sub-sector.
• Design and develop a rating system that allows for benchmarking across different deep tech verticals.
• Data Strategy, Sourcing & Engineering:
• Identify and integrate diverse data sources, including private investment databases (Crunchbase, PitchBook, Tracxn etc.), public records (ACRA, IPOS for patents), and talent networks (LinkedIn/Glints data).
• Collaborate with government partners (e.g. A*STAR, EnterpriseSG) and other partners in IHL's and industry to access and process relevant sector data.
• Build data processing and ingestion workflows to clean, transform, and interpret large datasets.
• Advanced Analytics & AI Implementation:
• Implement various AI/ML tools (e.g. AutoML, Natural Language Processing) to extract unstructured web data and perform data-driven sentiment analysis on ecosystem vibrancy and readiness.
• Use clustering algorithms to validate maturity stages and detect anomalies in the data.
• Collaborate with and report to SMU Principal Investigators to ensure the statistical validity and academic rigor of the framework.

Qualifications

• Preferably Master's or PhD in Economics, Statistics, Data Science, Finance, or a related quantitative fields.
• Statistical Analysis: Proficiency in R, Python, or Stata for econometric and statistical modeling and index construction.
• Data Engineering: Experience with SQL and data cleaning/transformation.
• AI/ML Familiarity: Experience with NLP (Natural Language Processing) and ML libraries (e.g. for sentiment analysis or clustering) is highly desirable.
• Tools: Familiarity with platforms like Databricks, Google Cloud BigQuery, or rapid data mining tools.
• Understanding of Innovation & Enterprise (I&E) metrics, venture capital (VC) terminology, and economic indicators.
• Ability to interpret data related to startup valuation, patent citations (IP), and talent flows.
• Translation: Ability to explain complex statistical concepts to non-technical stakeholders (government agencies, investors).
• Collaboration: Comfortable working in a hybrid environment between a government-owned institution (SGInnovate) and an academic institution (SMU).

Other Information

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Posted On 05 Feb 2026

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