Shape the future of intelligent personalization by leading machine learning initiatives that power user-centric recommendations. In this role, you’ll take ownership of the full modeling lifecycle—from exploratory analysis and feature development to deployment and ongoing monitoring—ensuring models perform reliably and deliver measurable business value.
What You'll Do
- Lead the development and optimization of machine learning models focused on personalization and recommendation systems.
- Identify opportunities where ML can enhance product experiences and guide prioritization with product and engineering partners.
- Perform in-depth data analysis to uncover patterns, engineer meaningful features, and validate assumptions through statistical testing.
- Ensure high standards of data quality across pipelines and advocate for best practices in data usage across teams.
- Train, evaluate, and fine-tune models using appropriate statistical and machine learning techniques.
- Deploy models into production using MLOps infrastructure and monitor for performance, data drift, and business impact.
- Communicate technical findings clearly to non-technical stakeholders, enabling data-informed decision-making.
- Document solutions thoroughly and contribute to improving team-wide technical standards and collaboration.
- Promote a strong data culture by sharing insights, mentoring peers, and supporting cross-team initiatives.
What We're Looking For
- Master’s or higher in a quantitative field such as Statistics, Computer Science, or Data Science.
- At least three years of professional experience applying machine learning in production environments.
- Strong coding skills in Python and SQL, with a focus on clean, efficient, and testable code.
- Proven understanding of statistical concepts including hypothesis testing, causal inference, and model validation.
- Experience working with cloud platforms—Google Cloud Platform (GCP) preferred.
- Familiarity with end-to-end ML development, from prototyping to deployment and monitoring.
- Excellent communication skills in English, with the ability to translate technical results into actionable insights.
- A collaborative mindset, with emphasis on empathy, active listening, and knowledge sharing.
- Self-driven approach with the ability to manage projects independently and deliver high-quality outcomes.
Nice to Have
- Prior experience in delivery, mobility, or financial services industries.
- Background in building ML-powered features for digital applications or web platforms.
