Data Scientist

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Amplify

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2000

📚 Education

☁️ SaaS

💰 Series C - Amplify Education on 2023-05

Education • SaaS

Amplify is a K–12 educational technology and curriculum company that builds next-generation, research-aligned curricula, assessments, and instructional tools for literacy, math, and science. Their offerings include core curricula (Amplify CKLA, Amplify ELA, Amplify Science), assessment and intervention products (mCLASS, Boost Reading, Boost Math), and digital/math resources (Amplify Desmos Math), plus tutoring and teacher professional learning resources. Amplify emphasizes the Science of Reading, provides an integrated digital platform for districts and teachers, and serves thousands of school districts and millions of students and teachers worldwide.

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

• competitive health insurance • mental health options • 401(k) plan • paid time off • parental leave • access to best-in-class development programs