Data Scientist

Amplify; United States; On-site; USD 100,000 - 132,000; Full time

Job summary

Amplify seeks an experienced Data Scientist to join our Supply Chain Analytics team, developing ML models to forecast demand, optimize inventory, and reduce costs across our educational product portfolio.

This role will drive data science best practices and introduce advanced analytics capabilities to support strategic supply chain decisions affecting tens-of-thousands of ISBNs and hundreds of millions in revenue every year.

Qualifications

• 2+ years in data science focused on supply chain forecasting or logistics.
• Strong time-series forecasting methods and Python data analysis.
• SQL proficiency for data analysis tasks and model evaluation.
• Experience deploying ML models to production (AWS SageMaker, Databricks).
• Git-based collaboration and writing clear technical documentation.
• Excellent written and spoken communication with non-technical partners.
• Ability to drive self-directed projects and cross-functional collaboration.

Responsibilities

• Train, test, and deploy ML models across the supply chain domain.
• Use advanced analytics to explain observations and recommend actions.
• Develop high-quality data products from ingestion to analysis and modeling.
• Lead knowledge sharing and propose tooling improvements within the team.

Skills

Forecasting

Time series

Python

SQL

ML deployment

Git

Communication

Cross-functional

Tools

Snowflake

Docker

Kubernetes

AWS SageMaker

Databricks

Snowpark ML

Job description

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. 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. For more information, visit Amplify.com.

We seek an experienced Data Scientist to join our Supply Chain Analytics team, developing Machine Learning models to forecast demand, optimize inventory, and reduce costs across our educational product portfolio. This role will drive data science best practices and introduce advanced analytics capabilities to support strategic supply chain decisions affecting tens-of-thousands of ISBNs and hundreds of millions in revenue every year. To accomplish this, the Data Scientist will work with a cross functional scrum team of Analytics Engineers and Data Analysts to build state of the art data products.

This Data Science role will report to our Data Science manager who leads Data Science for Amplify's Sales, Marketing and Finance departments. As such, they will be empowered to innovate and participate in important decisions across the entire data stack.

Essential Responsibilities

• Train, test, and deploy Machine Learning models: Drive the development of new Machine Learning capabilities by contributing at every stage of the Machine Learning delivery pipeline including research, evaluation, deployment and monitoring.
• Seek the why behind every observation: Use advanced data analysis techniques to construct compelling narratives and recommend actions and strategies that our Supply Chain team can make to improve operations.
• Work cross functionally to deliver superior data products: Contribute to development efforts from data ingestion, to data transformation, through to data analysis and machine learning in order to deliver high quality, impactful data products.
• Give back to the broader Data Science team: Help our Data Science team continuously improve by leading team learning sessions and proposing novel tooling or architectures.

Required Qualifications

• 2+ years of experience in a data science role working on Supply Chain forecasting or logistics optimization problems.
• Proficiency with statistical methods and especially time series forecasting methodologies (eg. SARIMA, prophet, xGBoost)
• Expert user of Python for data analysis tasks (data cleaning, manipulation, analysis).
• Expert user of SQL, especially its use in data analysis tasks.
• Experience training and evaluating the performance of machine learning models leveraging industry standard libraries like PyTorch, scikit-learn, tidymodels, xGBoost.
• Experience deploying machine learning models from research environments into production environments like AWS Sagemaker, Databricks or Snowpark ML.
• Demonstrated application of software development methodology and protocols, including using git for 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.

Preferred Qualifications

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

Amplify is an Equal Opportunity Employer. Amplify makes employment decisions based on qualifications and merit, and does not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability status, veteran status, or any other legally protected characteristic or status.

Amplify is committed to providing reasonable accommodations for qualified individuals with disabilities, including disabled veterans. If you have a disability and need an accommodation in connection with the application or hiring process, please email [e-mail].

If you are selected for employment, a background check will be required. As required by state and local laws and district policies, you may be required to provide additional documentation, such as proof of vaccination, or submit to enhanced background screening, such as fingerprinting.

Amplify is an E-Verify participant.

Compensation Range: $100K - $132K