Ryan is looking for a Manager of Data Science to lead and grow a team, translate complex tax and financial challenges into data science solutions, and deploy these solutions into production on Azure and Databricks.
Requirements
- Expert in Python (pandas, scikit-learn), deep-learning frameworks (PyTorch, TensorFlow, Keras)
- Experience fine-tuning and deploying transformer-based models (e.g. GPT, BERT) via Azure OpenAI or Hugging Face
- Azure Databricks (Spark, Delta Lake, Unity Catalog), Azure Data Factory
- MLflow, Azure ML pipelines, CI/CD (GitHub Actions or Azure DevOps), Docker/Kubernetes
- Terraform/ARM for infrastructure-as-code; monitoring with Azure Monitor or Prometheus
- SQL Server, Azure SQL, Cosmos DB, ADLS/Blob Storage
- Azure Form Recognizer or equivalent for structured/unstructured document extraction
Responsibilities
- Recruit, mentor, and retain a high-performing Data Science team (Data Scientists & Sr. Data Scientists), providing regular coaching, career-path guidance, and structured feedback.
- Oversee rapid iteration of POCs and MVPs on Databricks (Spark/Delta Lake) and Azure ML, from feature engineering and model training through evaluation and production deployment.
- Lead by example—write, review, and optimize Python notebooks and production code daily; troubleshoot performance bottlenecks and cost-optimize compute.
- Architect, develop, and deploy classification models on unstructured data (CNNs, RNNs, transformers) alongside tree-based and ensemble methods for structured data.
- Implement end-to-end NLP workflows—tokenization, embedding generation, LLM fine-tuning, and RAG frameworks—for document understanding and virtual assistants.
- Rapidly prototype and fine-tune GenAI solutions (Azure OpenAI, Hugging Face), collaborating with Data Engineering and MLOps (MLflow, Azure DevOps) to productionize successful pilots.
- Ensure code quality (unit tests, version control, documentation), embed responsible AI practices (bias detection, explainability, data-privacy compliance), monitor model drift, and maintain production SLAs.
Other
- Partner with Product Owners, Finance, and Tax leadership to define clear use cases, success metrics, and roadmaps that align with strategic goals.
- Translate complex technical findings into concise presentations and decision-ready recommendations for executive and business audiences.
- Exceptional communicator: translates technical concepts for executive and business audiences
- Strategic thinker: balances long-term AI roadmap with agile, iterative delivery
- Collaborative leader: thrives in cross-functional, matrixed teams
