Senior Data Scientist, Sales Forecasting & ML

Amplify; United States; Hybrid; USD 140,000 - 190,000; Full time

Job summary

Amplify, a leader in K–12 literacy and edtech, seeks a Senior Data Scientist for our Sales Analytics team. You will own sales forecasting across product lines and regions, turning insights into revenue and planning recommendations.

Report to the Data Science Manager and collaborate with Analytics Engineers and Data Analysts on end-to-end data products, shaping data strategy from modeling source data to deployment, monitoring, and explainability.

Qualifications

• 5+ years in data science with 3+ years in sales/demand forecasting.
• Proficient with Python or R for data tasks.
• Strong time series forecasting knowledge (ARIMA/Prophet/LSTM).
• SQL proficiency for data analysis tasks.
• Experience with ML libraries (PyTorch, scikit-learn, tidymodels, XGBoost).
• Experience deploying ML pipelines in production (AWS SageMaker/Databricks/Snowflake).
• Solid software-dev practices: version control and testing.
• Excellent written and verbal communication with non-technical partners.
• Experience mentoring data scientists and leading discussions.

Responsibilities

• Develop sales forecasting models across domains and horizons.
• Own end-to-end ML lifecycle: scoping, feature engineering, training, deployment, monitoring.
• Translate model outputs into actionable recommendations for leaders.
• Provide technical leadership: design reviews, learning sessions, roadmap input.

Skills

Data science experience

Python

R

SQL

Time series forecasting

ARIMA

Prophet

LSTM

ML libraries

ML pipelines

AWS SageMaker

Databricks

Snowflake

Version control

Communication

Mentoring

Education

Graduate degree in quantitative field

Tools

Docker

Kubernetes

Job description

Amplify, a leader in K–12 literacy and edtech, seeks a Senior Data Scientist for our Sales Analytics team. You will own sales forecasting across product lines and regions, turning insights into revenue and planning recommendations.

Report to the Data Science Manager and collaborate with Analytics Engineers and Data Analysts on end-to-end data products, shaping data strategy from modeling source data to deployment, monitoring, and explainability.