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Amplify Education is a K–12 education technology leader serving over 18 million students and teachers across all 50 states and six continents. The company builds inspiring teaching and learning experiences in literacy, biliteracy, math, and science through its Amplify Classroom platform, which combines curriculum, assessment, and supplemental learning.
You will join the Sales Analytics team as a Senior Data Scientist, owning sales forecasting and championing data-driven decision-making across the sales organization. Reporting to the Data Science Manager, you will work on a scrum team with Analytics Engineers and Data Analysts to ship data products end-to-end.
Key responsibilities include:
- Developing sales forecasting excellence by building statistical and machine learning models that meet forecasting needs across business domains, and contributing to self-service analytics tools so business partners can get answers independently.
- Owning the end-to-end machine learning lifecycle: scoping, feature engineering, model training and testing, deployment, monitoring, and explainability.
- Driving strategic business partnerships by translating model outputs into actionable recommendations for business leaders, identifying which drivers move the sales forecast and by how much.
- Providing technical leadership by mentoring junior data scientists, leading technical design reviews and learning sessions, and helping shape the team's roadmap and standards.
You will participate directly in decisions across the data stack, from planning how source data is modeled to innovating on solutions for the sales team.
REQUIREMENTS:
- 5+ years of experience in a data science role, with 3+ years focused on sales forecasting, demand forecasting, or revenue analytics. A graduate degree in a science or quantitative field (Computer Science, Economics, Math, Physics, Statistics) may count toward 2 of the 5 years.
- Expert user of Python or R for data analysis tasks (data cleaning, manipulation, analysis).
- Expert knowledge of time series forecasting methods (ARIMA, Prophet, LSTM).
- Proficiency with SQL for data analysis tasks.
- Proficient in training and evaluating machine learning models using industry-standard libraries (PyTorch, scikit-learn, tidymodels, XGBoost).
- Proven track record of developing and implementing machine learning pipelines running in production environments (AWS SageMaker, Databricks, Snowflake).
- Demonstrated application of software development methodology and protocols, including version control and testing.
- Excellent communication skills in writing and conversation, especially with non-technical partners.
- Experience driving self-directed projects and working cross-functionally.
- Experience mentoring other data scientists or leading technical discussions.
PREFERRED:
- Experience working with Snowflake.
- Experience with container technologies (Docker, Kubernetes).
- Background in education or edtech.
