Senior Data Scientist - Sales Analytics

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.

A pioneer in education since 2000, Amplify has developed deep relationships in states and districts by partnering with educators to drive implementation quality and improved outcomes. 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. Day-to-day, that means 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. 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.

Essential Responsibilities:

• Develop sales forecasting excellence: by building statistical and machine learning models that meet forecasting needs across business domains. Contribute to self-service analytics and data tools so that our business partners can get answers without waiting on the team.

• Own the end-to-end machine learning lifecycle: scoping, feature engineering, model training and testing, deployment, monitoring, and explainability.

• Drive strategic business partnerships: translate model outputs into actionable recommendations for business leaders, including which drivers move the sales forecast and by how much.

• Provide technical leadership: mentor junior data scientists, lead technical design reviews and learning sessions, and help shape the team's roadmap and standards.