Personal Requirements

• Bias for action & ownership - you’re comfortable owning analyses end‑to‑end and influencing product roadmaps with data‑backed recommendations 

• Curiosity & scientific rigor - formulate hypotheses, design experiments and measure impact with statistical discipline 

• Strong communicator & team player – explain complex models to cross‑functional stakeholders and collaborate closely with engineers, PMs and designers 

• Startup experience – thrive amid changing priorities and ship increments quickly to deliver business value

Technical Requirements

• 5 + years building & deploying ML/AI models in Python (pandas, scikit‑learn, TensorFlow/PyTorch) 

• Expert SQL skills plus familiarity with modern cloud data warehouses (BigQuery, Snowflake, Redshift) 

• Statistical experimentation & causal inference - design, power and analyse A/B & multivariate tests 

• Production‑grade data pipelines & MLOps - orchestrate batch/stream processing with tools like Airflow, Kafka or Spark; containerise and monitor models 

• Generative AI & LLMs - fine‑tuning, prompt engineering and evaluation of transformer‑based models (nice‑to‑have but strongly valued) with tools like Sagemaker or Bedrock

• Data visualisation & storytelling - build dashboards (e.g., Looker, Metabase) and craft narratives that drive decisions 

• Cloud engineering - hands‑on with at least one major provider (AWS, GCP, or Azure) and infrastructure‑as‑code practices 

• Bonus points for experience with real‑time event streams, reinforcement-learning-based personalisation, or privacy‑preserving ML