Machine Learning Engineer - Ads

6 days ago

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Connecting data scientists/engineers and companies, perfectly.

Marketplace for Hiring Data Scientists • Staffing & Recruiting • Machine Learning • Big Data • Analytics

11 - 50

Description

•Lead the development and refinement of predictive ML models, particularly Ad Score and Ad Account Health. •Conduct in-depth data analysis to identify trends, patterns, and insights that inform model development and optimization. •Collaborate with data engineers to create and maintain feature engineering pipelines to support model training. •Implement rigorous evaluation methodologies to assess model performance, making necessary adjustments for continuous improvement. •Work closely with engineering teams to deploy models and integrate them into our products through APIs. •Collaborate closely with product managers, full-stack engineers, and TPMs to ensure seamless integration of data science solutions into our products. •Stay up-to-date with the latest developments in the field of data science and machine learning and explore innovative approaches to problem-solving.

Requirements

•Master’s or Ph.D. in a related field with a strong academic background. •Proven experience as a Data Scientist with a track record of developing and deploying predictive ML models. •Expertise in machine learning techniques, including but not limited to regression, classification, clustering, and deep learning. •Proficiency in data manipulation, feature engineering, and model evaluation. •Strong programming skills in languages such as Python and experience with libraries like TensorFlow, PyTorch, or scikit-learn. •Excellent communication skills and the ability to collaborate effectively within cross-functional teams. •A passion for continuous learning and staying updated with the latest trends and technologies in data science. •Strong problem-solving abilities and the capacity to translate complex data into actionable insights.

Benefits

•Only open to US citizens and GC holders. •Hybrid work in Queens office 3 days per week.