Growth Marketing Operations Technical Specialist

Growth Marketing Operations Technical Specialist
Location: Hybrid onsite schedule in Culver City, CA
Schedule: 40 hours
Duration: 12 months
Pay: $45-$47.52 DOE

The Planet Group is looking for a Growth Marketing Operations Technical Specialist to join our well-known Fortune 500 client on a 12-months contract, working a hybrid onsite schedule in Culver City, CA.

Growth Marketing Operations Technical Specialist | Qualifications:

• At least 5-7 years in AI/ML design and implementation.
• Strong experience in designing, developing, and implementing AI and ML models (including deep learning and neural networks) to address business problems and enhance decision-making.
• Experience with Large Language Models (LLMs) integration and techniques such as prompt engineering.
• Solid foundation in languages such as Python (with libraries like Pandas, NumPy, Scikit-learn), R, and SQL.
• In-depth knowledge of machine learning algorithms (e.g., regression, classification, clustering, decision trees, random forests, neural networks) and frameworks (e.g., TensorFlow, PyTorch).
• Skills in data wrangling (cleaning, transformation), feature engineering, and data manipulation.
• Proven track record of challenging the status quo through data-driven results and strong cross-functional execution.
• Skilled in data analysis and creating insightful visualizations using tools like Tableau.

Growth Marketing Operations Technical Specialist | Description:

• The ideal candidate brings a wealth of knowledge and experience in AI/ML and analytics for marketing operations and execution. You have experience with SAS/CRM and are comfortable with complex ecosystem issues. Your primary focus will be on developing insights to inform ecosystem and CRM improvement opportunities.
• Lead AI/ML design, implementation, and optimization to identify ecosystem patterns and solve business and operational problems.
• Extract insights and build predictive systems to inform decision making. This involves selecting appropriate algorithms, performing feature engineering, and evaluating and fine-tuning model performance.
• Own end-to-end AI/ML technical development in roadmap/scoping, model creation, API integration, data collection integrity, and data pipeline management. * Validate data integrity and accuracy throughout the analysis lifecycle, ensuring findings are reliable and decision-ready.
• Maintain dashboards and design automated reports that deliver timely, accurate insights to both technical and non-technical audiences.
• Collaborate with cross-functional teams, including data engineers, software engineers, and business stakeholders, to identify opportunities for AI/ML applications and communicate findings to non-technical audiences.
• Curiosity, adaptability, collaboration, business acumen, and attention to detail are also highly valued.