Data Scientist II
Tasks
- Analyze structured and unstructured datasets
- Apply time-series forecasting techniques
- Build forecasting models
- Collaborate with stakeholders on hypotheses and KPIs
- Deploy models using MLOps
- Design analytical workflows
- Frame experiments and define experiment frameworks
- Ideate analytical and machine learning solutions
- Mentor junior data scientists
- Monitor and document models
- Partner with engineering teams for data pipelines
- Present model recommendations to technical and non technical audiences
- Prototype analytical and machine learning solutions
Perks/Benefits
- N/A
Skills/Tech-stack
ARIMA | AWS | Agentic AI | Artificial Intelligence | Azure | BigQuery | CI/CD | Causal Inference | Containerization | Data Pipelines | Databricks | Experimental Design | Git | Google Cloud | Holt-Winters | Hypothesis Testing | LLM Agents | Language Models | Language Processing | Large Language Models | MLflow | Machine Learning | Matplotlib | Model Monitoring | Natural Language | Natural Language Processing | NoSQL | Plotly | Power BI | Prophet | Python | Reproducibility | SQL | Seaborn | Series forecasting | Snowflake | Spark | Statistical modeling | Tableau | Time Series | Time Series Forecasting
Education
Roles
Data Scientist | Data Scientist II | Scientist | Scientist II
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