Predictive Modeling Data Scientist

Zimmerman Advertising

United States

United States

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À propos

The Predictive Modeling Data Scientist will collaborate with Retail Technology, Media, and Account Services teams to enhance our Marketing, Direct, and Digital efforts through innovative predictive modeling solutions. We are seeking a driven individual with a strong analytical mindset and a passion for making a significant impact on business outcomes. This is a unique opportunity to join a dynamic and diverse analytics department that is committed to leveraging data science for enhanced business strategies. Key Responsibilities: Assist the Lead Data Scientist and the data science team in developing solution accelerators, establishing effective pipelines, and integrating with LLM Products on the Databricks platform. Utilize ML flow or similar tools to create and serve machine learning models effectively. Work closely with cross-functional teams, including data scientists, product managers, data engineers, and software engineers, to design, develop, and deploy machine learning models that align with our business goals. Ensure the development and maintenance of continuous integration and delivery pipelines for machine learning models, validating and deploying them consistently and reliably. Conduct data analysis and feature engineering to support the development of advanced machine learning models. Stay current with the latest advancements in machine learning and MLOps, evaluating emerging technologies that can enhance our processes and models. Mentor and provide technical guidance to junior data scientists and machine learning engineers, fostering their professional growth. Leverage open-source tools to build frameworks and components that improve and scale our Serving and ML platform. Qualifications: Proven experience in architecting and hands-on implementation of infrastructure solutions. A strong background in the Media, Advertising, or Marketing industry is essential. Ability to deploy machine learning models to a production cloud environment. Hands-on experience with GCP, Databricks, or Apache Spark is mandatory. Solid understanding of ETL concepts and data processing workflows. Experience with machine learning libraries and predictive analytics techniques. Proficient in AWS Sagemaker, Kafka, Python, R, SQL and NoSQL Databases, Spark, Scikit-Learn, Keras/TensorFlow, PyTorch, Docker, CI/CD Pipelines, Git, and API development. Degree in Computer Science or a related field. A minimum of 1 year of industry experience in developing scalable services and data-driven platforms. Expertise in building ML infrastructure, writing production-level code, and deploying machine learning models. Experience tackling complex problems and systems where scalability and performance are critical. Strong problem-solving abilities and debugging skills, with a passion for AI ethics and understanding causality.

United States

Compétences linguistiques

English

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