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# Senior Data Scientist

- **Company:** IDR, Inc.
- **Location:** Conshohocken, PA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Agile Methodology, Airflow, Amazon Web Services, Big Data, Continuous Integration, Information Engineering, Python (Programming Language), Machine Learning, Tensorflow, SQL Databases, Google Cloud, Cloud Platform System, Pytorch, Large Language Models, Scikit Learn, Information Technology, Machine Learning Operations, Data Pipelines
- **Published:** October 13, 2026
- **Apply:** https://www.dice.com/job-detail/54dbfba5-90dd-4299-8d2e-f35c9fd7d3fe

## About the Role

* 5+ years of experience in Data Science, Machine Learning, or a closely related field
 * Strong proficiency in Python and SQL, including experience working with large datasets
 * Hands-on experience with modern ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
 * Experience deploying and supporting models in production using MLOps/automation tools (e.g., MLflow, Airflow, CI/CD workflows, monitoring)
 * Experience working in cloud environments (AWS and/or Google Cloud Platform) with a strong foundation in statistics, probability, and experimentation (e.g., A/B testing)
 * Master's in Computer Science, Mathematics, Engineering, or a related technical field, or equivalent relevant experience. PHD highly preferred.

## Description

IDR is seeking a Data Scientist to join one of our top clients for an opportunity in Conshohocken, PA. This role focuses on building and deploying machine learning solutions that improve personalization, automation, and data-driven decision-making across digital products. You'll collaborate closely with data engineering, product, and business stakeholders in a fast-paced, Agile environment to deliver measurable outcomes., * Develop, optimize, and deploy machine learning models that support personalization and automation initiatives

 * Partner with data engineers and product teams to design scalable data pipelines and workflows
 * Implement reliable model deployment, monitoring, and maintenance practices to support production ML systems
 * Apply advanced AI techniques (including generative AI/LLMs) to improve user engagement and operational effectiveness
 * Communicate methodologies, results, and recommendations clearly to both technical and non-technical stakeholders