Senior Data Scientist

Company Description

Responsibilities

• Frame ambiguous business problems as well-defined ML problems with clear success criteria.
• Design, build, and ship end-to-end ML and generative AI systems in production. You handle data pipelines, feature engineering, model training, serving, and monitoring without handoffs.
• Architect robust ML-based systems. Write clean, scalable production code. Train, deploy, and maintain reliable models.
• Leverage LLMs and generative AI for data enrichment, content understanding, and automated decision-making within production systems.
• Design and analyse experiments rigorously (A/B and multivariate tests) to measure model and product impact.
• Develop deep familiarity with source data and its generating systems through collaboration with engineering teams and systematic profiling.
• Provide high-quality insights and data-driven recommendations to drive strategic organisational choices.
• Mentor other data scientists. Elevate engineering and ML best practices — improving our ways of working, tooling, MLOps, and internal training.
• What we're looking for:
• 3+ years shipping production ML systems (generative AI, recommendation engines, or ML infrastructure). Demonstrated velocity and ownership.
• Strong software engineering fundamentals: clean code, solid grasp of data structures, and system design (both general and ML-specific).
• Hands-on with the ML lifecycle: problem formulation, data auditing, modelling, deployment, interpretation, presentation.
• Proficiency in Python and SQL. Comfort with reproducible analysis and experimentation (A/B and multivariate analysis). Solid statistical thinking.
• Experience building data and training pipelines (Airflow or equivalent). Strong feature engineering and data modelling skills.
• Production ML systems experience: building, deploying, serving, monitoring. You understand MLOps practices.
• Familiarity with product data (events, impressions, conversions, engagement, retention). You know how to measure product health.
• Experience with LLMs and NLP-based solutions for data enrichment and automation is a plus.
• BigQuery or equivalent cloud data warehouse experience is a plus. GCP familiarity is a plus but not required.