Lead Data Scientist - MLOps

The Role :

As a Lead Data Scientist, you'll be responsible for end-to-end ownership of critical data science products, from conceptualization and model development to deployment in a production environment.

You will lead projects focused on areas like customer churn prediction, recommendation systems, and dynamic pricing optimization, directly impacting key business metrics.

What You'll Do :

- Model Development : Design, train, and evaluate highly accurate machine learning models (Classification, Regression, NLP, Deep Learning) to solve complex business problems.

- MLOps & Deployment : Work with DevOps/MLOps teams to implement and manage CI/CD pipelines for ML models, ensuring reliable and scalable production deployment.

- Feature Engineering & Data Cleaning : Master complex, large-scale datasets, focusing on advanced feature engineering and data transformation.

- Stakeholder Communication : Translate complex analytical findings and model results into clear, actionable insights and compelling visualisations for non-technical stakeholders.

- Research & Innovation : Stay abreast of the latest advancements in AI/ML research and propose new methodologies or technologies to maintain a competitive edge.

Required Skills & Qualifications :

- 6+ years of experience in Data Science, with a focus on building and deploying ML models in a commercial setting.

- Expert proficiency in Python (Pandas, NumPy, Scikit-learn) and ML frameworks (TensorFlow/PyTorch).

- Exceptional skills in SQL for data extraction and manipulation.

- Proven experience with MLOps tools (e.g., MLflow, Kubeflow) and cloud platforms (AWS SageMaker, GCP AI Platform).

- Deep statistical knowledge and experience with A/B testing and experimental design.

- Master's or PhD in a quantitative field (Computer Science, Statistics, Mathematics)