Senior Data Scientist - Amplify

About Amplify

Amplify helps teachers bring delight and rigor to students every day. We have become a leader in K–12 literacy, biliteracy, math, and science by building inspiring teaching and learning experiences based on research. The Amplify Classroom platform combines curriculum, assessment, and supplemental learning into one coherent high-quality instructional system. Today, Amplify serves more than 18 million students and teachers across all 50 states and on six continents.

We are hiring a Senior Data Scientist for our Sales Analytics team. You will own sales forecasting and champion data-driven decision making across our sales organization, analyzing sales trends, building models that predict sales across product lines and regions over different time horizons, and turning those forecasts into recommendations for revenue and planning decisions.

You will report to our Data Science Manager and work on a scrum team with Analytics Engineers and Data Analysts, shipping data products end-to-end.

Essential Responsibilities

• Develop sales forecasting excellence: Build statistical and machine learning models that meet forecasting needs across business domains. Contribute to self-service analytics and data tools so business partners can get answers independently.
• Own the end-to-end machine learning lifecycle: Handle scoping, feature engineering, model training and testing, deployment, monitoring, and explainability.
• Drive strategic business partnerships: Translate model outputs into actionable recommendations for business leaders regarding sales drivers and forecasts.
• Provide technical leadership: Mentor junior data scientists, lead technical design reviews and learning sessions, and help shape the team's roadmap and standards.

Required Qualifications

• 5+ years of experience in a data science role, with 3+ years focused on sales forecasting, demand forecasting, or revenue analytics (graduate degree in a quantitative field may count toward 2 years).
• Expert user of Python or R for data analysis tasks (data cleaning, manipulation, analysis).
• Expert knowledge of time series forecasting methods (e.g., ARIMA, Prophet, LSTM).
• Proficiency with SQL for data analysis tasks.
• Proficient in training and evaluating machine learning models using industry-standard libraries like PyTorch, scikit-learn, tidymodels, and XGBoost.
• Proven track record of developing and implementing machine learning pipelines running in production environments like AWS SageMaker, Databricks, or Snowflake.
• Demonstrated application of software development methodology and protocols, including version control and testing.
• Excellent written and verbal communication skills, especially with non-technical partners.
• Experience driving self-directed projects and working cross-functionally.
• Experience mentoring other data scientists or leading technical discussions.

Preferred Qualifications

• Experience working with Snowflake.
• Experience with container technologies (e.g., Docker and Kubernetes).
• Background in education or in edtech.