Senior Data Science Engineer

November 10

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Logo of RightEye

RightEye

Eye tracking • Performance Improvement • Predictive Analytics • Big Data Modeling • Vision Testing

11 - 50 employees

⚕️ Healthcare Insurance

📚 Education

⚽ Sports

💰 $1M Debt Financing on 2020-03

Description

• Responsible for end-to-end development of production ready machine learning models • Experience in data extraction, cleaning, EDA, model decision making, model development, tuning and productionizing • Demonstrated experience in productionizing ML models • Ability to generalize and validate models • Creating algorithm prototypes based on project specifications • Experience in developing projects from concept to production • Running tests to assess model performance • Implementing changes to algorithms to improve model performance • Troubleshooting and addressing problems with deployed ML models to improve user experience • Documenting all steps in the development process • Remaining up to date on the latest innovations in machine learning • Assembling large, complex sets of data that meet non-functional and functional business requirements • Identifying, designing, and implementing internal process improvements, optimizing data delivery, and automating manual processes • Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS and SQL technologies • Building analytical tools to utilize the data pipeline, providing actionable insights • Working with stakeholders including data, design, product, and executive teams and assisting them with data-related technical issues • Working with stakeholders including the Executive, Product, Data, Engineering and Design teams to support their data infrastructure needs while assisting with data-related technical issues

Requirements

• 5+ years in a Data Science and Engineering role • Experienced Python developer • Experience with using machine learning frameworks such as pycharm, pytorch, AWS SageMaker • Experience with SDLC for machine learning (building, testing, and production deployments) • Demonstrated ability to build resilient, scalable and secure code • AWS SQL and NoSQL databases • Developing data pipelines from scratch

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