Job Title: Data Scientist
Industry: Technology / Digital Media & Services
Location: Remote – must be local to Cupertino, CA or Culver City, CA
Duration: 12 months; potential to extend – W2 Contract
Schedule: Full-time | 40 hours per week
Position Overview
The Planet Group is looking for a Data Scientist to join a well-known Fortune 500 client on a 12-month contract, working remotely but must be local to Cupertino or Culver City, CA.
Must Have
• Bachelor’s degree in Data Science, Computer Science, Engineering, or a related field
• Strong foundation in probability and statistics
• Proficiency in SQL and Python or R to work with large data sets
• Knowledge around supervised and unsupervised machine learning algorithms (regression, classification, clustering, decision trees, neural networks, etc.)
• Hands-on experience leveraging LLMs to solve business problems, such as classification, data analysis, and data labeling
• Understands digital marketing data and KPIs – Social, SEO, Paid Media, etc.
• Looking for someone with 3–5 years of experience manipulating data sets and using statistical / ML models to extract insights and visualize them for stakeholders
Nice to Have
• Ability to apply causal inference for marketing, and familiar with marketing mix modeling or multi-touch attribution models
• Knowledge of model evaluation frameworks including metric definition, sampling strategy, and human-in-the-loop processes
• Proficiency in code collaboration / version control systems (Git, GitHub, GitLab)
Disqualifiers
• No exposure to digital marketing data or KPIs
• No hands-on experience with ML models in a business setting
Day-to-Day / Job Overview
• Maintain and improve existing ML/NLP models (Python-based) used for campaign forecasting, trend analysis, and consumer feedback classification
• Enhance LLM classification workflows through prompt tuning, QA, and human-in-the-loop review
• Work closely with influencer, editorial, and performance marketing teams to translate model outputs into actionable insights
• Support causal impact analysis of marketing efforts to inform strategy
Description
• Build and maintain machine learning models to forecast and optimize campaign performance, identify trends and key drivers
• Produce performance benchmarks across various digital marketing channels by evaluating both internal and competitor performance
• Improve existing LLM classification workflow by fine-tuning prompts, QA data quality, and implementing human-in-the-loop review
• Maintain data analytics dashboards in Tableau, Power BI, or similar BI platforms
• Assess business needs to translate model outputs into tangible and actionable findings and reports for both marketing and product
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