Data Scientist – Tax Digital Innovation
Deloitte's Tax Digital Innovation team is a key strategic function within the tax and legal business and includes several future‑looking capabilities that help drive exciting and innovative growth opportunities. In the role of Data Scientist within our expanding AI & Data Studio you will work on new and existing projects, delivering insights to clients and utilising data to make smarter, better decisions.
- Proactively source external structured and unstructured data sets to enhance services and insights
- Process, cleanse, and verify the integrity of data used for analysis
- Perform ad‑hoc analysis and present results from a business‑centric perspective
- Build innovative models to classify and predict tax and legal data leveraging state‑of‑the‑art machine learning and deep learning techniques
- Design, build and test data pipelines for machine learning that are reliable, scalable, and easily deployable
- Take ownership of models, from initial build through to model maintenance, avoiding performance drift over time
- Track model performance constantly
- Clearly articulate the value and benefits of delivering analytics projects to clients
- Work closely with Tax and Legal SMEs to build deep understanding of business/client challenges and develop proofs of concept
- Share, communicate and develop bespoke AI solutions
- Drive automation and optimisation of business workflows to help clients increase efficiency
Essential Qualifications
- Strong understanding of statistical modelling, supervised/unsupervised machine learning algorithms
- Ability to explain model operations to non‑technical audiences and advocate for interpretability and audit best practices
- Experience working with structured and unstructured datasets
- Proficient in Python, using key data science libraries (NumPy, Pandas, scikit‑learn) and object‑oriented programming principles to develop efficient, scalable solutions
- Hands‑on experience experimenting with Generative AI (e.g. LangChain, Hugging Face, LlamaIndex)
- Experience working with Azure data & AI services such as Azure Machine Learning and Azure Foundry
- Practical experience working in Agile environments and contributing to sprints, stand‑ups and backlog refinement
- Experience writing clean, well‑structured documentation for models and analytical workflows
- Familiarity with version control (Git) and collaborative coding practices
- Strong communication and teamwork skills
- Evidence of translating R&D theoretical concepts into business scenarios
Desirable Qualifications
- Microsoft Azure Data Scientist Associate (DP‑100) certification or equivalent
- Strong understanding of MLOps/DevOps concepts including model versioning, CI/CD, automated retraining, lineage and governance
- Experience with model risk management, Responsible AI and compliance controls in regulated industries
- Knowledge of model evaluation, testing and reliability checks
- Familiarity with deep learning frameworks such as TensorFlow or PyTorch
- Experience with data visualisation tools such as PowerBI and Tableau
- Experience deploying models into production using Azure services
- Exposure to data engineering fundamentals (e.g., data pipelines, delta lake)
- Knowledge of experience‐tracking tools (MLflow, Azure ML tracking)
Contact Details:
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