About Role:
The Product Insights Analyst owns end-to-end insight products that help commercial, medical, and content teams (and clients) make faster, clearer decisions. The role bridges product performance, client needs, and advanced analytics to strengthen Docquity's commercial service offerings across Southeast Asia, translating business questions into scalable dashboards, recurring reports, and analyses supported by robust data models. This is, first and foremost, an analytics and insight role; familiarity with the engineering that brings insight products to life (data architecture, backend, frontend, and AWS deployment) is a welcome bonus and a growth opportunity rather than a core expectation.
Job Description:
- Build and own dashboards and insight products end-to-end (requirements, metric design, data logic, QA, deployment, documentation, and iteration), aligned to decision use-cases.
- Translate analyses into decision-ready outputs: interpretation guidance, clear recommendations, and what to do next actions (e.g., content planning, campaign optimization, segment strategies).
- Develop and maintain analytical models (e.g., scoring/segmentation, intent, content impact, uplift/movement tracking) and contribute to experimentation frameworks.
- Conduct deep-dive studies on platform, product, and campaign performance; produce recurring analyses such as audience movement, funnel conversion, and cohort/retention trends.
- Build, enhance, and innovate AIDE modules for client use cases; identify opportunities to develop new data-driven products or services.
- Collaborate cross-functionally to translate business objectives into analytical frameworks and measurable KPIs; partner with data/platform teams to strengthen pipelines and data quality.
- Ensure governance and quality (version control, documentation, monitoring for anomalies/drift) and drive adoption through stakeholder training and supporting materials.
- Use AI tools responsibly to accelerate analysis, documentation, and QA, ensuring outputs are validated, explainable, and compliant with confidentiality and data-handling standards.
Experience/ Skills Required:
- Bachelor's degree in a quantitative field (Data Science, Statistics, Mathematics, Computer Science, Engineering, or related).
- 5+ years of experience in data analysis, business intelligence, or product analytics; healthcare/pharma or regulated-industry experience is a plus.
- Strong SQL skills and proficiency in Python (R a plus) for analysis and automation.
- Experience building dashboards in Tableau, Power BI, Streamlit, or Apache Superset with a focus on clarity and usability.
- Understanding of data modelling/ETL concepts and working with large, complex datasets.
- Experimentation and applied ML (causal inference, segmentation/uplift modeling).
- Comfort with AI-assisted tools (copilots, LLM-based assistants) with strong judgment for validation and data privacy.
- Strong communication and stakeholder management skills; able to translate technical analyses into actions, and comfortable working across multicultural teams and time zones (occasional travel may be required).
- Nice-to-have: data architecture/modeling depth (dbt, Airflow), backend frameworks (FastAPI/Flask/Node.js), frontend development (React/TypeScript), and AWS deployment (Lightsail/EC2, Docker, CI/CD, Nginx, Linux administration).
Culture at Docquity While we have been growing fast, we are still small enough that everyone makes a pivotal difference. We care less about hours worked and more about the outcome — and the impact you make. We have worked hard to create an autonomous working culture emphasizing work/life balance and a fun working environment. We follow the hybrid work culture.
