Experienced Data Scientist working on a new initiative to build and deploy a modelling solution to predict & optimise advertising campaign performance as part of a productionised, customer-facing SaaS product. Ideally looking for experience in Media/Advertising sector or similar.
Experience - Must-haves:
Must have a number of years working commercially as a Data Scientist
Solid understanding of & real-world experience implementing data science & statistical principles - e.g. applied statistics, model selection, cross-validation, objective functions, hyperparameter tuning, continuous & discrete optimisation problems, etc.
Strong interpersonal skills & ability to explain data science principles with clarity to non-technical stakeholders when required
Extensive knowledge of Python programming principles including object-oriented programming, performance optimisation
Experience developing & deploying productionised Machine Learning applications on a cloud platform (GCP ideal, AWS & Azure also acceptable)
Experience with common Python packages for Machine Learning - examples include PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas, etc.
Strong knowledge of SQL and its use for data preparation & feature engineering
Understanding of & practical experience with implementing MLOps principals - including automated model retraining, monitoring & deployment strategies
Some knowledge of containerisation & use of tools like Docker & Docker Compose
Nice-to-haves (Mix of the following but not all essential):
Experience working with Google Cloud products for ML including Vertex AI Pipelines & BigQuery
Experience with dbt (data build tool)
Previous experience working with advertising data
Experience with FastAPI or other Python API frameworks
Experience with dashboarding tools such as Looker Studio, Tableau or PowerBI
Experience working on a SaaS (Software-as-a-Service) application
Experience working with Kubeflow Pipelines
Experience developing on a Mac / Unix environment
Knowledge of CICD pipeline design & implementation
Experience modelling using GenAI, LLMs or neural networks in general
A/B testing experience / Statistical hypothesis testing experience