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# Senior Data Scientist

- **Company:** Recruiting from Scratch
- **Location:** Los Angeles, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $110,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Python (Programming Language), Machine Learning, Software Construction, Feature Engineering, Pytorch, Prophet, Snowflake, Scikit Learn, Xgboost, Machine Learning Operations, Software Version Control, Recurrent Neural Networks, Docker, Databricks
- **Published:** November 3, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-data-scientist-los-angeles-ca--53014c0d-ff0f-44d7-b416-9cca31fe2b0f

## About the Role

Data Science, Mathematics, Training/Teaching Curriculum, Literacy, Predictive Modeling, Teachers Help, Sales Forecasting, Machine Learning, Revenue Forecasting, Forecasting, * 5+ years of experience in data science, machine learning, or quantitative analytics

 * Strong background in sales forecasting, revenue analytics, or time-series modeling
 * Expertise with forecasting methodologies such as ARIMA, Prophet, LSTM, or related approaches
 * Advanced proficiency in Python or R for data analysis and machine learning workflows
 * Strong SQL expertise for analytical and modeling use cases
 * Experience training and evaluating machine learning models using frameworks such as PyTorch, scikit-learn, xGBoost, or equivalent
 * Proven experience deploying machine learning systems into production environments such as AWS SageMaker, Databricks, or Snowflake
 * Strong understanding of software engineering best practices including version control and testing
 * Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders
 * Comfortable operating independently in highly cross-functional environments

Preferred

 * Experience with Snowflake
 * Familiarity with Docker and Kubernetes
 * Experience within education technology or education-focused organizations
 * Prior experience building forecasting systems at scale across multiple business units or markets

## Description

* Build and improve sales forecasting models across multiple product lines and geographic regions
 * Develop statistical and machine learning solutions for short-term and long-term revenue forecasting
 * Own the full machine learning lifecycle including feature engineering, training, deployment, monitoring, and explainability
 * Create self-service forecasting tools that enable real-time decision-making across business teams
 * Translate model outputs into actionable business recommendations and strategic insights
 * Partner cross-functionally with analytics engineers, analysts, and business stakeholders
 * Mentor junior data scientists and contribute to technical standards, reviews, and team best practices
 * Influence forecasting strategy and drive data-informed planning across the organization