[Hiring] Data Scientist @Siemens

Role Description

We are looking for a hands-on Data Scientist to transform asset, maintenance, operational, and product data into production-ready analytical and machine learning solutions. In this role, you will partner with product managers, engineers, domain experts, and customer-facing teams to:

• Frame business problems
• Prepare data
• Develop and evaluate models
• Support deployment into production workflows

You will independently own well-defined data science workstreams and be accountable for the quality, explainability, and measurable impact of your work. This role is ideal for someone with strong applied statistics, Python, SQL, and machine learning experience who can move effectively from exploration and experimentation to validated, production-ready solutions. This is a remotely based role in the U.S.

Qualifications

• 4-5 years of professional experience in data science, applied machine learning, predictive analytics, or a closely related field.
• Bachelor's or Master's degree in Computer Science, Statistics, Data Science, Machine Learning, Operations Research, Applied Mathematics, Engineering, or a related quantitative discipline.
• Demonstrated experience delivering data science or machine learning solutions beyond exploratory prototypes, including at least one solution deployed to a product, operational process, or recurring business workflow.

Requirements

• Strong proficiency in Python and relevant libraries such as pandas, NumPy, scikit-learn, XGBoost, PyTorch, or TensorFlow.
• Strong working proficiency in SQL, including joins, aggregations, window functions, and analysis of production-scale datasets.
• Applied knowledge of statistics, probability, hypothesis testing, feature engineering, model validation, performance measurement, and interpretability.
• Experience with supervised and unsupervised machine learning methods including regression, classification, clustering, tree-based models, anomaly detection, and forecasting.
• Experience preparing and validating imperfect real-world data, including missing values, inconsistent definitions, outliers, leakage risks, and data quality issues.
• Familiarity with Git, code review, testing, documentation, and reproducible development practices.
• Experience using at least one cloud or enterprise data platform such as Azure, AWS, GCP, Snowflake, Databricks, or a comparable environment.
• Familiarity with model deployment or MLOps concepts such as model registries, experiment tracking, batch or API inference, monitoring, and retraining workflows.
• Ability to communicate technical results clearly and connect analytical work to customer, product, or operational outcomes.
• Ability to work effectively across product, engineering, domain, and business teams.

Benefits

• Siemens offers a variety of health and wellness benefits to our employees.
• The pay range for this position is $86,485 - $148,261 annually. The actual wage offered may be lower or higher depending on budget and candidate experience, knowledge, skills, qualifications, and premium geographic location.

Company Description

At Siemens, we help organizations transform maintenance and operations through connected insights, AI-powered technology, and intelligent asset management solutions. Our software enables customers to manage the full lifecycle of assets, facilities, and infrastructure while improving efficiency, reducing risk, and optimizing long-term investments. By connecting data, people, and processes, we empower organizations to make smarter decisions, maximize asset performance, and achieve more resilient operations.