About Supermom
Supermom connects modern mothers in Southeast Asia to parenting brands, powered by data and AI. We operate a parenting community across Singapore, Malaysia, and Indonesia, and we are evolving from a media and community business into a data and AI-first parenting intelligence platform.
We are building a unified intelligence layer that draws on first-party app data, community conversation signals, creator-network data, and global parenting data, and turns it into value for two audiences: parenting brands who want sharper audience insight, and mothers who use our AI parenting assistant for trusted, community-grounded guidance.
The Role
We are hiring a Data Scientist to design and own the data strategy behind this intelligence layer. This is a hands-on, end-to-end role: you build the data pipeline, engineer the signals, and turn them into both commercial insight products and product features. You will own the work from raw data through to business outcome, working directly with senior leadership.
This is an applied, builder role. The value is created through strong data engineering, high-quality data matching, and a clear translation of signals into business and product outcomes, rather than through research-grade modelling alone. A second analytics hire is planned to support this role as the function grows.
What You Will Own
Data pipeline and engineering
Build, run, and maintain a multi-source data pipeline on a modern cloud data warehouse. Own ingestion, scheduling, monitoring, and data quality end to end. Match and reconcile signals across sources of different reliability, and activate finished audiences through our marketing stack.
Signal engineering and audience building
Turn raw behavioural and conversational data into structured, well-documented audience signals with clear thresholds and confidence levels. Build audience segments that are defensible, auditable, and tied to real use cases.
Conversational and unstructured data
Build natural-language pipelines over large volumes of multilingual conversational data across our markets, extracting topics, intent, sentiment, and emerging trends in a privacy-safe and aggregated form.
Commercial insight products
Turn the unified signal layer into repeatable insight reports, strategy recommendations, and advisory outputs that brands value, rather than one-off bespoke analyses.
AI product differentiation
Feed community-grounded signals into our AI parenting assistant so its answers are locally relevant and community-centric, in a way a generic assistant cannot match.
Governance
Uphold data legality, privacy, consent, and clear data lineage across all markets. Never expose individual user identifiers in any output.
What We Are Looking For
Required
- 4 to 7 years in data science, analytics engineering, or a closely related applied role.
- Strong, cost-aware SQL on a cloud data warehouse (BigQuery or equivalent): window functions, complex joins, large-scale data handling.
- Python for building production data pipelines and analysis, with experience of scheduled, monitored jobs.
- Experience with entity resolution, data matching, and a strong data-quality discipline.
- Natural-language processing experience on unstructured text, ideally multilingual.
- A track record of acquiring and integrating data from varied sources, with sound judgement on what is appropriate and permitted.
- The ability to translate technical signals into a clear commercial and product narrative for senior stakeholders.
Preferred
- Background in marketing analytics, adtech, or audience intelligence.
- Experience integrating signals into a customer data platform and into an AI or retrieval-grounded product.
- Comfort working bilingually in English and Chinese.
- Familiarity with data-protection and consent frameworks in Southeast Asia.
Why This Role
You will design the data strategy for a regional parenting platform from an early and formative stage, with direct access to leadership and clear ownership of both the engineering and the strategy. The work spans commercial impact and product impact, and the signals you build become a long-term, compounding asset for the business.
Hiring Process
Round 1: an informal meet and greet to understand your background and motivation.
Round 2: a short case presentation.
Final discussion: role terms and compensation.
