Data Scientist

(Junior level role | 1–3 years' experience)About the firmJanuary Capital is an established venture capital manager headquartered in Singapore. At January Capital, we seek to invest in technology businesses that will power growth in the Asia-Pacific region over the coming decades. We're inspired by those individuals who are willing to dedicate themselves to solving some of the region's biggest challenges and challenge the status quo. Today, we are proud to have partnered with more than 60 exceptional companies, including Tazapay, Great Question, Skedulo, GO1, Akulaku, Shopback, Marqo and aCommerce. We manage more than US$450 million of assets on behalf of our investors, who comprise leading institutions, foundations, family offices and individuals.About the roleData is at the core of everything we do at January Capital. We are building a continuously updating world model of ambitious people and the companies they create—a temporal graph that spans careers, not just current roles. The core thesis is that people are more persistent and predictive than the companies they found. By tracking individuals across their full arc to date, we surface signal earlier than any reactive competitor. There are a multitude of data points across Asia Pacific, and this role will help synthesise those signals and extract incremental value from the data.As a Junior Data Scientist, you'll join the Data Science & ML squad, turning the raw signal flowing through the graph (people moves, company events and funding activity) into analysis the investment team can act on. This is a hands-on, analysis-heavy role. You won't own model architecture on day one, but you'll be doing real work against real data from week one: exploring datasets, validating pipeline output, building features, and helping quantify what actually predicts a good investment.Working closely with the Data Engineer, product managers and the investment team,you'll contribute across three key areas:Investment intelligence & analysis – Analyse people, company and signal data across the graph to identify what correlates with a strong investment outcome. Build and iterate on features that feed scoring and signal models, and help test hypotheses about which signals—such as career moves, hiring velocity, product launches and funding events—predict the "moment of maximum signal."Data quality & pipeline support – Validate data quality coming out of ingestion pipelines, working closely with the Data Engineer. Write ad hoc SQL and Python analysis to answer investment-team questions about coverage, freshness and signal recall, and help maintain internal dashboards for pipeline health and model performance.Cross-functional collaboration – Work with the investment team and product managers across the firm, and present interesting findings back to the investment team clearly, without hiding behind jargon.You'll receive direct mentorship from veteran engineers and investors in this space, as well as exposure to how a top-tier early-stage VC fund evaluates companies and people. You'll have real ownership of analysis that feeds decisions the investment team makes every week while working on a proprietary temporal graph product. The role offers a competitive salary and equity in a product built to become a standalone company.What we are looking for:Required1-3 years of experience in data science or analytics (strong internships count).Strong SQL and Python (Pandas, scikit-learn or similar).Solid grounding in statistics—comfortable reasoning about sample size, bias, and correlation vs. causation.Comfortable working with messy, real-world data: entity resolution issues, missing values, duplicate records.Genuine curiosity about company and people data, and how it connects to venture investing—prior VC experience favourable.Nice to haveExposure to graph data structures or network analysis.Familiarity with private markets or startup ecosystems.Experience working in a small, fast-moving startup environment.