The Predictive Analytics Data Scientist will work collaboratively with our Retail Technology, Media, and Account Services teams to revolutionize our Marketing, Direct, and Digital initiatives through cutting-edge predictive modeling solutions. We are looking for a motivated individual with a strong analytical mindset and a desire to make a meaningful impact on business outcomes. Join our dynamic and diverse analytics department, which is focused on harnessing data science to elevate business strategies.
Key Responsibilities:
• Support the Lead Data Scientist and the data science team in creating solution accelerators and establishing efficient pipelines, integrating with LLM Products on the Databricks platform.
• Utilize tools like ML flow to effectively build and deploy machine learning models.
• Collaborate with cross-functional teams, including data scientists, product managers, data engineers, and software engineers, to design and implement machine learning models that meet our business objectives.
• Maintain continuous integration and delivery pipelines for machine learning models, ensuring consistent and reliable validation and deployment.
• Conduct in-depth data analysis and feature engineering to advance the development of sophisticated machine learning models.
• Stay abreast of the latest advancements in machine learning and MLOps, assessing new technologies that could enhance our processes and models.
• Offer mentorship and technical guidance to junior data scientists and machine learning engineers, promoting their professional growth.
• Use open-source tools to develop frameworks and components that enhance and scale our Serving and ML platforms.
Qualifications:
• Demonstrated experience in architecting and implementing infrastructure solutions.
• A solid background in the Media, Advertising, or Marketing industry is essential.
• Proficiency in deploying machine learning models to a production cloud environment.
• Hands-on expertise with GCP, Databricks, or Apache Spark is necessary.
• Strong grasp of ETL concepts and data processing workflows.
• Experience with machine learning libraries and predictive analytics methodologies.
• Skilled in AWS Sagemaker, Kafka, Python, R, SQL and NoSQL Databases, Spark, Scikit-Learn, Keras/TensorFlow, PyTorch, Docker, CI/CD Pipelines, Git, and API development.
• Bachelor's degree in Computer Science or a related field.
• A minimum of 1 year of industry experience in building scalable services and data-driven platforms.
• Expertise in constructing ML infrastructure, writing production-level code, and deploying machine learning models.
• Experience in solving complex problems where scalability and performance are crucial.
• Strong problem-solving skills along with debugging abilities, and a keen interest in AI ethics and understanding causality.
