Senior Data Scientist
$170,000–$220,000 year
On-siteNew York, United States or Manhattan, New York, United States
Job Summary
Design, develop, and deploy predictive classification, regression, and anomaly detection models while conducting extensive EDA, feature engineering, and data preprocessing. Evaluate model performance using statistical techniques, execute A/B tests to validate impact, and perform customer segmentation via clustering algorithms. Collaborate with Product, Engineering, and Marketing teams to integrate ML solutions into workflows, work with ML Engineering to ensure scalable data pipelines, and establish model governance through monitoring dashboards. Analyze diverse datasets to extract actionable insights for optimization. This role is based in NYC with a base salary range of $170,000 to $220,000.
Required Qualifications
- 5+ years of experience in data science with a strong emphasis on machine learning modeling
- Proficiency in Python for data analysis and ML, with experience using libraries such as Scikit-Learn, XGBoost, TensorFlow, or PyTorch
- Expertise in SQL and working with large, complex structured and semi-structured datasets
- Strong understanding of core machine learning techniques, including logistic regression, gradient boosting, decision trees, and clustering methods
- Experience in feature engineering, model selection, and performance optimization
- Experienced in designing, executing, analyzing, and reporting on experiments
- Strong communication skills and ability to present findings to technical and non-technical stakeholders
Desired Qualifications
- Master's or higher degree in Data Science, Computer Science, Statistics, or a related field is preferred
- Experience working in fintech, e-commerce, or other data-rich consumer-facing industries
- Familiarity with Google Cloud Platform (GCP) services, particularly Vertex AI and Dataflow, for scalable data processing and model training
- Experience with dbt for data modeling
- Familiarity with BigQuery or other MPP (Massively Parallel Processing) databases
- Experience using the Scala programming language for developing scalable and efficient data pipelines
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