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Data Scientist II
Skills
Computer ScienceAmazon RedshiftData MiningData ScienceGoogle BigqueryMachine LearningNatural Language Processing
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Bachelor’s Degree in Computer Science, Data Science, Statistics, or a related field
- 3 years of experience developing traditional machine learning models using Python and applying advanced algorithms
- 2+ years of hands-on experience working with data warehouse systems such as Snowflake, BigQuery, and Redshift to support data-driven model development
- Willingness to travel to the Oakland office monthly to collaborate with other Earnies
Nice to have
- Computer Science
- Amazon Redshift
- Data Mining
- Data Science
- Google Bigquery
- Machine Learning
- Natural Language Processing
- Pattern Recognition
- Predictive Analytics
- Python
- Data Warehouse
- ETL
- Pipelines
- Feature Engineering
- Model Selection
- Validation
- Stakeholder Management
- Data Querying
- Recommendations
- Snowflake
- BigQuery
- Redshift
- Scikit-learn
- TensorFlow
- PyTorch
Day to day
- You will design and implement ETL pipelines to ingest data from operational systems, third-party sources, and public datasets into the data warehouse
- You will transform existing data for user consumption, and source data for model training
- You will extract data for model training from various sources, including data warehouses such as Earnest and Navient, production databases, third-party providers, and publicly available datasets
- You will prototype machine learning models by applying best practices in feature engineering, model selection, and validation
- You will write efficient code using popular frameworks such as Scikit-learn, TensorFlow, and PyTorch
- You will articulate to stakeholders the impact of the models and analyses through presentations and reports
- You will draft recommendations for stakeholders that would optimize the product and underwriting policies
Hiring process
- Read more below, and let’s build something great together
