TripleLift
Data Scientist
New York, US•2 months ago
$90K – $120K
data sciencemachine learningpython
Data Science1 month agoOn-site
Raptive
Data Scientist
data sciencereal time advertisingSnowflakeHivePrestoBigQueryPythonBashAWSNumPyscikit-learnRTensorFlowKerasPyTorchXGBoostconvolutional neural networkscontainerizationorchestrationmachine learningprogrammatic
Key details
Salary
$100K – $150K
Employment type
Full-time
Seniority
Mid-level
Years experience
3-5
Location
New York, US
Full job description
Raptive seeks a Data Scientist for the RevOps Data Science team to analyze large data sets and deliver insights to drive business decisions. Responsibilities include designing experiments to improve revenue, classifying audience and content for sales support, providing floor price guidance, visualizing systems, and understanding data generation processes. Candidates must have a graduate degree or equivalent in Statistics, Industrial Systems Engineering, or related fields, familiarity with real-time advertising markets, experience with large data processing tools (Snowflake, Hive, Presto, BigQuery), scripting (Bash, Python), AWS, statistical software (NumPy, scikit-learn, R), machine learning libraries (TensorFlow, Keras, PyTorch), and deploying models in production environments. U.S. work authorization without visa sponsorship is required. Salary range is $100,000-$150,000.
What you'll do
- Design and analyze experiments to improve revenue
- Classify audience and content to support programmatic direct and indirect sales
- Deliver evolutionary floor price guidance
- Visualize complex systems
- Build deep understanding of data generating processes
Requirements
- Graduate degree or equivalent in Statistics, Industrial Systems Engineering, or comparable field
- Familiarity with real time advertising markets
- Experience processing large data sets (e.g. Snowflake, Hive, Presto, BigQuery)
- Scripting experience (e.g. Bash, Python)
- Experience with AWS environment
- Experience with statistical software (e.g. NumPy, scikit-learn, R)
- Familiarity with classification and regression libraries (e.g. TensorFlow, Keras, PyTorch)
- Familiarity with algorithms such as XGBoost, Convolutional Neural Networks
- Experience deploying, scaling, and maintaining data science models in production environments
- Experience with cloud platforms, containerization, orchestration or related tools
- Authorized to work for any employer in the U.S. without visa sponsorship
Tech stack
SnowflakeHivePrestoBigQueryBashPythonAWSNumPyscikit-learnRTensorFlowKerasPyTorchXGBoostConvolutional Neural Networkscontainerizationorchestration
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