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# Data Scientist IRC307997

- **Company:** GlobalLogic
- **Location:** San Jose, CA, United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Automation of Tests, Unit Testing, Microsoft Azure, Configuration Management, Continuous Integration, Monitoring of Systems, Python (Programming Language), Machine Learning, Recommender Systems, Software Deployment, Data Logging, Feature Engineering, Sql Optimization, Git, Data Lakes, Git Flow, Comarch, Machine Learning Operations, Drift Detection, Model Registry, Streamlit Framework, Databricks
- **Published:** November 5, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pwodwlguby

## About the Role

* You have expert-level Python skills for end-to-end data science and production machine learning, from feature engineering to inference.
 * You possess advanced SQL capabilities for querying complex customer, transaction, campaign, margin, and measurement datasets.
 * You bring extensive hands-on experience delivering production ML on Databricks, leveraging notebooks, modular code, Delta Lake, Unity Catalog, and the model registry.
 * You demonstrate proven proficiency in professional software practices, including Git branching strategies, CI/CD with Azure DevOps, unit testing, and reproducible deployments.
 * You have a deep understanding of uplift modeling, statistical matching, experimentation design, and operations research or constrained optimization.
 * You ideally bring familiarity with interactive front ends (such as Databricks Apps or Streamlit), Databricks Asset Bundles, MLflow, and enterprise CRM platforms like Salesforce Marketing Cloud or Comarch.

## Description

We are looking for a Data Scientist to direct the design, development, and operationalization of our enterprise customer decision-science and optimization platform. In this role, you will take ownership of advanced causal modeling, campaign recommendation engines, offer economics, and budget-constrained decisioning pipelines running in production., * Lead the design, experimentation, and production deployment of customer decisioning, causal/uplift models, and recommendation algorithms.

 * Develop mathematical optimization frameworks to balance campaign economics, margin constraints, and contact budgets across audiences.
 * Build, deploy, and scale robust production ML pipelines on Databricks using Unity Catalog, automated workflows, and scheduled scoring jobs.
 * Establish engineering rigor across the team through structured Git workflows, pull request reviews, automated testing, and controlled release cycles in Azure DevOps.
 * Implement end-to-end MLOps standards, including configuration management, model monitoring, logging, drift detection, and operational handover.
 * Partner with engineering and business stakeholders to design analytical decision-support tools and translate complex campaign economics into operational rules.