About the role
We are now looking for a professional to join our Regional Business Strategy and Insights department for Viu, a leading pan-regional OTT video service with presence across Asia, the Middle East, and South Africa.
As a Senior Data Scientist on the Data Science and Engineering team, you will drive data-driven decision-making and develop advanced models that power user engagement, personalisation, and subscriber growth across our OTT streaming platform. You will lead high-impact data initiatives that enhance product, content, and marketing decisions across the organization. You will be involved in the full lifecycle of data science projects, from exploratory analysis and feature development to modeling, validation, and collaborating with engineering teams to deploy solutions into production. This role is ideal for someone who thrives in fast-paced consumer tech environments and enjoys solving complex, large-scale problems. As a regional role, you will work closely with cross-functional partners across markets and contribute to Viu's data transformation journey.
Key Responsibilities
- Build predictive and behavioural ML models to understand user intent, content affinity, and support key business outcomes.
- Drive experimentation (A/B testing, uplift modelling) to validate model and product impact.
- Conduct deep-dive analyses on user behaviour, retention cohorts, and content performance.
- Translate complex analytical findings into actionable business insights for Product, Growth, and Content teams.
- Operationalise models with cross-functional teams, including CRM and Product, to integrate outputs into campaigns, rails, and in-product experiences.
- Communicate recommendations clearly to stakeholders, influencing strategy and product decisions.
What you'll need to succeed
- Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or related field.
- 3+ years experience in Data Science, Machine Learning, or Applied Analytics.
- Strong proficiency in Python, SQL, and data manipulation frameworks.
- Hands-on experience building and evaluating ML models (classification, recommendation, time-series, uplift).
- Experience in experimentation design and statistical analysis.
- Solid understanding of data pipelines, feature stores, and model deployment workflows.
- Ability to translate complex technical work into clear business impact.
- Exposure to MLOps or ML Engineering pipelines (Airflow, Kubeflow, SageMaker, etc.).
- Familiarity with data engineering tools (Spark, BigQuery, Snowflake, Databricks).
- Domain experience in the digital marketing, e-commerce, CRM, MarTech or AdTech fields is preferred
- Experience with marketing activation platforms (Braze, CRM systems) is a plus.
