Data Science & Engineering Lead
Tasks
- Architect lakehouse solutions
- Build NoSQL solutions
- Build and deploy ML models
- Create BI dashboards
- Deploy ML pipelines in production
- Design ETL processes
- Design neural network architectures
- Develop NLP and computer vision models
- Develop data pipelines
- Develop database models
- Enhance model performance
- Implement GPU acceleration
- Implement time-series models
- Manage cloud infrastructure
- Mentor team members
- Optimize data systems
Perks/Benefits
Skills/Tech-stack
API Gateway | AWS | Airbyte | Airflow | Azure | Azure ML | Big Data | Big-data frameworks | CNN | CUDA | CloudFormation | Computer Vision | DBT | Data Frameworks | Deep learning | Delta | Distributed Training | DynamoDB | ETL | Elasticsearch | GAN | GPU Acceleration | Great Expectations | Iceberg | Kafka | Kinesis | Lakehouse Architecture | Lambda | Language Processing | Machine Learning | MongoDB | Natural Language | Natural Language Processing | Neural Networks | NoSQL | NumPy | OpenCV | Pandas | PowerBI | PyTorch | RNN | Relational databases | Retrieval-Augmented Generation | SQL | SageMaker | Scikit-learn | Series modeling | Tableau | TensorFlow | Terraform | Time Series | Time Series Modeling | Transformers
Education
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