Data Science Engineer

WorkGenius Group; Culver City (CA); On-site; USD 95,000 - 140,000; Full time

Job summary

WorkGenius Group in Culver City, CA is seeking a Data Science Engineer to design, develop, validate, and deploy ML models for marketing forecasting and budget optimization. You will build response models, time-series forecasts, and Generative AI solutions including LLM agents and retrieval systems.

You will own the full ML lifecycle from feature engineering to production deployment, monitoring, drift detection, and retraining, collaborating with stakeholders to communicate assumptions and

Qualifications

• Experience deploying ML solutions for marketing analytics, forecasting, estimation, or media optimization.
• Advanced Python skills with pandas, NumPy, scikit-learn, and SQL/data warehouse experience.
• Strong foundation in statistics, experimentation, uncertainty quantification, backtesting, model validation, and forecasting.
• Hands-on experience managing production ML pipelines and the complete ML lifecycle, including deployment, monitoring, data quality checks, and retraining with Apache Airflow.
• Experience building Generative AI solutions, including LLMs, tool-calling workflows, and embeddings.

Responsibilities

• Design, develop, validate, and deploy ML models for marketing forecasting, campaign estimation, media planning, and budget optimization.
• Build marketing response models with response curves, diminishing-returns analysis, and budget allocation recommendations.
• Develop time-series forecasting, resource estimation, predictive modeling, and Generative AI solutions (LLM agents, retrieval systems, MCP servers, and entity resolution).
• Own end-to-end ML lifecycle: feature engineering, production deployment, monitoring, drift detection, retraining, evaluation.
• Build and maintain production ML pipelines with Apache Airflow; communicate assumptions and results to stakeholders.

Skills

Machine Learning

Marketing Analytics

Forecasting

Python

Statistical Modeling

Apache Airflow

Generative AI

LLM Agents

Retrieval-Augmented Generation

Model Monitoring

Tools

Prophet

PyMC

Stan

Job description

• Design, develop, validate, and deploy machine learning models for marketing forecasting, campaign estimation, media planning, and budget optimization.
• Build marketing response models incorporating response curves, diminishing-returns analysis, marginal efficiency, and budget allocation recommendations.
• Develop time-series forecasting, resource estimation, predictive modeling, and Generative AI solutions, including LLM agents, retrieval systems, MCP servers, and entity resolution workflows.
• Own the end-to-end machine learning lifecycle, including feature engineering, production deployment, monitoring, versioning, drift detection, retraining, and model evaluation.
• Build and maintain production ML pipelines with Apache Airflow and Python services; collaborate with stakeholders to communicate modeling assumptions, results, and recommendations.

Title: Data Science Engineer

Industry: Technology

Location: Culver City, CA

Duration: 18 months

Responsibilities

• Design, develop, validate, and deploy machine learning models for marketing forecasting, campaign estimation, media planning, and budget optimization.
• Build marketing response models incorporating response curves, diminishing-returns analysis, marginal efficiency, and budget allocation recommendations.
• Develop time-series forecasting, resource estimation, predictive modeling, and Generative AI solutions, including LLM agents, retrieval systems, MCP servers, and entity resolution workflows.
• Own the end-to-end machine learning lifecycle, including feature engineering, production deployment, monitoring, versioning, drift detection, retraining, and model evaluation.
• Build and maintain production ML pipelines with Apache Airflow and Python services; collaborate with stakeholders to communicate modeling assumptions, results, and recommendations.

Requirements

• Demonstrated experience developing and deploying machine learning solutions for marketing analytics, forecasting, estimation, or media optimization.
• Advanced Python skills with pandas, NumPy, scikit-learn, and statsmodels, plus strong SQL and data warehouse experience.
• Strong foundation in statistics, experimentation, uncertainty quantification, backtesting, model validation, and forecasting or probabilistic modeling using tools such as Prophet, PyMC, or Stan.
• Hands-on experience managing production ML pipelines and the complete ML lifecycle, including deployment, monitoring, data quality checks, and retraining with Apache Airflow.
• Experience building Generative AI solutions, including MCP servers, LLM agents, tool-calling workflows, prompt engineering, structured outputs, LLM evaluation, embeddings, vector databases, RAG, or entity resolution.

Skills

• Machine Learning
• Marketing Analytics
• Forecasting
• Python
• Statistical Modeling
• Apache Airflow
• Generative AI
• LLM Agents
• Retrieval-Augmented Generation
• Model Monitoring

Hourly rate is commensurate with experience and is an estimated range provided by WorkGenius.