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Senior Data Scientist

Posted about 2 months agoViewed

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💎 Seniority level: Senior, At least 8 years of experience in machine learning

📍 Location: United States

🔍 Industry: Data science, AI-driven consumer insights

🏢 Company: Resonate👥 101-250💰 Private over 2 years agoAdvertisingDigital MediaPredictive AnalyticsBrand MarketingMarketing Automation

🗣️ Languages: English

⏳ Experience: At least 8 years of experience in machine learning

🪄 Skills: PythonMachine LearningPyTorchData scienceTensorflow

Requirements:
  • Strong foundation in statistics, probability, and mathematics, with demonstrated proficiency in at least one of the following: TensorFlow, PyTorch, or JAX.
  • Proficient in Python and familiar with R (or a willingness to learn).
  • Proven experience in Machine Learning Ops, particularly in deploying and managing models in production environments.
  • A scientific mindset with the ability to solve problems through research, experimental design, hypothesis testing, and analysis.
  • Exceptional communication and collaboration skills, enabling you to explain complex concepts to non-technical audiences effectively.
  • A commitment to staying updated on the latest trends in deep learning and machine learning.
Responsibilities:
  • Build and deploy machine learning models to tackle complex business challenges, particularly in predictive analytics, segmentation, forecasting, and classification.
  • Work alongside fellow Data Scientists and ML Engineers to develop robust data and model pipelines, ensuring seamless integration and efficiency.
  • Assist in deploying models into production and monitor their performance while adhering to high governance standards.
  • Identify and recommend new machine learning applications within the organization, conducting research to uncover novel use cases.
  • Collaborate with the Product organization to create innovative products and solutions that meet business needs.
  • Understand and adhere to ethical principles in machine learning, ensuring fairness and mitigating bias in model development.
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