Senior Data Scientist
Tasks
- Apply pattern recognition techniques
- Build metrics dashboards
- Clean data pipelines
- Collaborate with cross-functional teams
- Create technical documentation
- Deploy machine learning models
- Design machine learning models
- Develop generative AI solutions
- Develop predictive analytics solutions
- Ensure data quality
- Execute A/B testing experiments
- Implement anomaly detection methods
- Monitor data pipelines
- Optimize information analysis products
- Orchestrate data pipelines
- Report model performance
- Run statistical experimentation
- Train machine learning models
- Translate business problems to data science use cases
- Validate data pipelines
- Validate machine learning models
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | ARIMA | AWS | Anomaly Detection | AutoEncoder | Azure | B testing | Clustering | Credit Risk | Cross-validation | Data Quality | Databricks | Deep learning | Document Classification | Fraud Detection | GCP | Hadoop | Isolation Forest | LLMs | Local Outlier Factor | MLOps | Machine Learning | Matplotlib | Milvus | NLP | NLP for Document Classification | Neural Networks | NoSQL | PGVector | Pattern Recognition | Pinecone | Plotly | Power BI | Prophet | PyTorch | Python | R | Recurrent Neural Networks | Robust Statistics | SQL | Scikit-learn | Seaborn | Spark | Supervised Learning | Tableau | TensorFlow | Time Series | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
Regions
Countries
States
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