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# Data Scientist

- **Company:** Siemens AG
- **Location:** Malvern, PA, United States
- **Experience:** Experienced
- **Salary:** $126,740.0 - $174,262.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Information Engineering, Python (Programming Language), Machine Learning, SQL Databases, Cloud Platform System, Generative AI, Front End Software Development, Virtual Agents, Databricks
- **Published:** November 8, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=6d725ddef8b35a93

## About the Role

We are seeking a mid-level Data Scientist with strong analytical skills, critical thinking, and communication abilities. The ideal candidate can solve complex business problems, collaborate effectively across Data Science, Data Engineering, and Front-End Development, and demonstrate the potential to grow into a technical leadership role. Experience with Databricks, CRM/ERP data environments, and healthcare is preferred., * Strong proficiency in Python, SQL, statistics, and machine learning.

 * Practical understanding of AI, including generative AI and its applications and limitations.
 * Strong critical thinking, problem-solving, and communication skills.
 * Experience collaborating with cross-functional technical teams.
 * Ability to work independently, exercise sound technical judgment, and demonstrate leadership potential., * Bachelor's degree
 * 5 to 8 years of experience
 * Experience with Databricks or similar cloud-based data platforms.
 * Experience working with CRM and ERP data, including integration and data consistency challenges.
 * Experience in healthcare or related industries.
 * Experience contributing to technical solution design or leading analytical initiatives.

## Description

* Translate business problems into actionable analytical and technical solutions.
 * Develop and implement statistical models, machine learning solutions, and AI-driven applications.
 * Collaborate with Data Engineering and Front-End Development to ensure solutions integrate effectively into existing systems.
 * Evaluate data quality, assumptions, technical trade-offs, and downstream impacts.
 * Clearly communicate technical concepts, findings, and recommendations to technical and nontechnical stakeholders.
 * Take ownership of solutions from problem definition through implementation.