Senior Data Scientist, Sales Forecasting & ML

Amplify; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Amplify is hiring a Senior Data Scientist for the Sales Analytics team. You will own sales forecasting, build models across product lines and regions, and turn forecasts into actionable recommendations for revenue planning.

You will report to the Data Science Manager and collaborate with Analytics Engineers and Data Analysts on end-to-end data products, contributing to data stack decisions and dashboarding for business partners.

Qualifications

• 5+ years in data science with 3+ years in sales/demand forecasting or revenue analytics.
• Expert in Python or R for data analysis.
• Strong time series forecasting methods (ARIMA, Prophet, LSTM).
• SQL proficiency for data analysis.
• Experience with ML libraries: PyTorch, scikit-learn, tidymodels, XGBoost.
• Experience deploying ML pipelines in production (AWS SageMaker, Databricks, Snowflake).
• Strong communication with non-technical partners.
• Experience mentoring data scientists and leading technical discussions.

Responsibilities

• Develop sales forecasting models and enable self-service analytics.
• Own end-to-end ML lifecycle: scope, features, training, deployment, monitoring, and explainability.
• Translate model outputs into actionable recommendations for business leaders.
• Provide technical leadership: mentor, design reviews, roadmap, and standards.

Skills

Sales forecasting

Time series forecasting

Python/R

SQL

Machine learning

ML pipelines

Version control

Communication

Cross-functional collaboration

Mentoring

Education

Graduate degree in quantitative field

Tools

Snowflake

Docker

Kubernetes

AWS SageMaker

Databricks

Job description

Amplify is hiring a Senior Data Scientist for the Sales Analytics team. You will own sales forecasting, build models across product lines and regions, and turn forecasts into actionable recommendations for revenue planning.

You will report to the Data Science Manager and collaborate with Analytics Engineers and Data Analysts on end-to-end data products, contributing to data stack decisions and dashboarding for business partners.