Harnham
Senior Data Scientist
Our client, a growing mid‑sized marketing ed‑tech company, is looking for a Senior Data Scientist to build advanced ML models for lead scoring, customer journey optimization, and Marketing Mix Modeling (MMM). Key Responsibilities
Develop and optimize ML models for lead scoring, customer journey mapping, and multi‑touch attribution analysis Design MMM frameworks to measure marketing channel effectiveness and optimize budget allocation Build end‑to‑end scalable data pipelines using Azure Databricks for large‑scale processing and Dagster for workflow orchestration Deploy production models via Kubernetes containerization and manage MLOps lifecycle Integrate LLMs and GenAI tools for content personalization, automated insights, and enhanced customer segmentation Conduct A/B testing and statistical analysis to validate model performance and business impact Create executive dashboards and collaborate with marketing, product, and business teams on data‑driven strategy Requirements
7+ years in data science with proven experience in marketing analytics, customer analytics, or related domains Expertise in Python (pandas, scikit‑learn, TensorFlow/PyTorch) and advanced SQL proficiency Hands‑on experience with Azure Databricks for distributed computing and collaborative analytics Proficiency with Dagster or similar workflow orchestration tools for data pipeline management Experience deploying ML models using Kubernetes and containerized applications Familiarity with LLMs, GenAI tools, and their practical applications in marketing All applicants must be authorized to work in the United States to qualify. Our client is unable to accommodate sponsorship at this time.
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Our client, a growing mid‑sized marketing ed‑tech company, is looking for a Senior Data Scientist to build advanced ML models for lead scoring, customer journey optimization, and Marketing Mix Modeling (MMM). Key Responsibilities
Develop and optimize ML models for lead scoring, customer journey mapping, and multi‑touch attribution analysis Design MMM frameworks to measure marketing channel effectiveness and optimize budget allocation Build end‑to‑end scalable data pipelines using Azure Databricks for large‑scale processing and Dagster for workflow orchestration Deploy production models via Kubernetes containerization and manage MLOps lifecycle Integrate LLMs and GenAI tools for content personalization, automated insights, and enhanced customer segmentation Conduct A/B testing and statistical analysis to validate model performance and business impact Create executive dashboards and collaborate with marketing, product, and business teams on data‑driven strategy Requirements
7+ years in data science with proven experience in marketing analytics, customer analytics, or related domains Expertise in Python (pandas, scikit‑learn, TensorFlow/PyTorch) and advanced SQL proficiency Hands‑on experience with Azure Databricks for distributed computing and collaborative analytics Proficiency with Dagster or similar workflow orchestration tools for data pipeline management Experience deploying ML models using Kubernetes and containerized applications Familiarity with LLMs, GenAI tools, and their practical applications in marketing All applicants must be authorized to work in the United States to qualify. Our client is unable to accommodate sponsorship at this time.
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