Data Scientist

🕒 March 3

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Amplify

1001 - 5000 employees

Founded 2000

📚 Education

💰 Series C on 2023-05

Education

Amplify is a pioneering company in K–12 education, dedicated to providing next-generation curriculum and assessment solutions. Since 2000, Amplify has been developing programs that empower educators with powerful tools, facilitating the development of comprehensive literacy and math systems for students in thousands of school districts globally. Their suite includes the Amplify CKLA literacy program, Desmos Math, and Amplify Science, all designed to align educational practices with the Science of Reading and evidence-based strategies. Amplify also offers professional development through podcasts and webinars, supporting teachers with insight and innovation.

📋 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

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

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