Director, Data Science
245 Summer St, Boston MA, United States
USD 126K-255K Executive-level Full Time
Tasks
- Add observability debugging and incident response
- Analyze impact of AI implementations on upstream and downstream systems
- Build and maintain retrieval-augmented generation systems
- Build data infrastructure for real-time and batch processing
- Collaborate with platform infrastructure and application teams
- Define monitor AI performance metrics aligned with business KPIs
- Deploy manage AI ML models on AWS
- Design deploy production ready AI and ML solutions
- Design implement ETL pipelines for structured and unstructured data
- Design scalable maintainable observable solutions
- Develop optimize large language model applications
- Document system dependencies data lineage and architecture
- Ensure data quality, governance, and security
- Establish monitoring for model performance and drift
- Implement MLOps continuous integration and deployment
- Implement context engineering and prompt optimization
- Optimize model serving for latency throughput and cost
- Perform exploratory data analysis
- Research prototype emerging AI techniques for production viability
- Translate business challenges into technical solutions
Perks/Benefits
- N/A
Skills/Tech-stack
API contracts | AWS | Airflow | Anaconda | Classification | Clustering | Context engineering | DBT | Data Lineage | Dimensionality Reduction | Drift Detection | EC2 | ETL | Embeddings | Fine Tuning | Flask | Hugging Face | Lambda | Langchain | Language Models | Large Language Models | MLOps | Machine Learning | Model Drift | Model Drift Detection | Model Monitoring | NumPy | Observability | Pandas | Pip | Predictive Modeling | Prompt engineering | Python | Regression | Retrieval-Augmented Generation | S3 | SageMaker | Scikit-learn | Semantic Search | Series analysis | Snowflake | Spark | Statistical modeling | Time Series | Time Series Analysis | Vector Databases
Roles
Regions
Countries
States
Cities
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