Senior Data Scientist (Sales Analytics) at Amplify

Amplify helps teachers bring delight and rigor to students every day. They are a leader in K–12 literacy, biliteracy, math, and science, 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. Since 2000, Amplify has developed deep relationships in states and districts, serving over 18 million students and teachers across all 50 states and six continents.

Amplify is hiring a Senior Data Scientist for their Sales Analytics team. You will own sales forecasting and champion data-driven decision-making across the sales organization. Daily tasks include analyzing sales trends, building models to predict sales across product lines and regions over different time horizons, and translating forecasts into revenue and planning recommendations.

You will report to the Data Science Manager and work on a scrum team with Analytics Engineers and Data Analysts, shipping data products end-to-end. Participation in decisions across the data stack, from data modeling to innovating solutions for the sales team, is expected.

Essential Responsibilities:

• Develop sales forecasting excellence by building statistical and machine learning models tailored to business domains. Contribute to self-service analytics and data tools to empower business partners with timely insights.

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

• Drive strategic business partnerships by translating model outputs into actionable recommendations for business leaders, identifying key drivers of sales forecasts and their impact.

• Provide technical leadership, mentoring junior data scientists, leading technical design reviews and learning sessions, and shaping 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. A graduate degree in a quantitative field (e.g., Computer Science, Economics, Math, Physics, Statistics) may count toward 2 of the 5 years.

• Expert user of Python or R for data analysis tasks, including data cleaning, manipulation, and analysis.

• Expert knowledge of time series forecasting methods, such as ARIMA, Prophet, and LSTM.

• Proficient in SQL for data analysis tasks.

• Proficient in training and evaluating machine learning models using libraries like PyTorch, scikit-learn, tidymodels, and XGBoost.

• Proven track record of developing and implementing machine learning pipelines in production environments like AWS SageMaker, Databricks, or 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 Qualifications:

• Experience working with Snowflake.

• Experience with container technologies, such as Docker and Kubernetes.

• Background in education or edtech.