Robotic Process Automation Specialist
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Staff Data Scientist, Computer Vision – Robotics Specialist
Siemens Healthineers
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $156,500 - $234,800 per year
Job Level
Lead
Tech Stack
PySparkPyTorchScikit-LearnSparkTensorflow
About the role
- Design, develop, and deploy ML models and traditional 2D and 3D computer vision approaches for robotic vision tasks (object detection, segmentation, classification, 2D and 3D measurements)
- Design, develop, deploy, and maintain end-to-end automated data processing pipelines. This includes data ingestion, data mining, exploratory analysis, transformation, storage, modelling, automation, and basic optimization
- Create, deploy, and maintain BI dashboards to communicate insights across the organization and promote data-driven decision making
- Design, develop, and deploy ML models for predictive and prescriptive maintenance, clinical decision support, and text analysis and information extraction
- Build prototypes for feasibility studies in healthcare environments and communicate results to stakeholders
- Conduct exploratory data analysis across diverse data types (machine data, EHRs, sensor data, logs, images)
- Collaborate across departments to optimize product performance using statistical and analytical rigor, as well as input from subject matter experts across a complex organizational structure
- Contribute to developing organizational best practices in machine learning and data science
Requirements
- Master's level university degree in mathematics, statistics, computer science, physics, electrical engineering or engineering sciences
- 5+ years of experience in data science and/or computer vision
- High level of expertise in big data, structured and unstructured data, Spark/PySpark, Delta Lake, and Databricks environment
- Strong technical expertise in technologies, algorithms, and methodologies in the areas of object detection (e.g., YOLO framework) and image analysis, deep neural networks architectures for object detection
- Experience with NVIDIA Omniverse environment and NVIDIA foundation models such as GR00T and Cosmos
- Substantial expertise in traditional computer vision and image analysis, for instance, utilizing OpenCV
- Deep expertise in leveraging and extending BI tools such as Power BI and Databricks dashboards (especially with complex data models)
- Technical expertise in technologies, algorithms and methodologies in the areas of transformer architecture, natural language processing, LLMs, copilots, and GenAI
- Understanding of concepts of time-series analysis, feature engineering, dimensionality reduction, etc.
- Ability to apply analytical rigor and statistical methods to optimize products
- High level of expertise in applied ML frameworks such as PyTorch, TensorFlow, Hugging Face, Scikit-learn, etc.
- Understanding of ML model explainability and ML risk assessment concepts
- Broad understanding of ML life cycle management/MLOps
- Practical skills in GPU ML training and inference
- Medical applications experience is preferred but not required
- Exceptional communication skills and mastery of visual storytelling with data
- High comfortability with navigating ambiguous problems, translating broad stakeholder requests into necessary actions, and independently driving data initiatives to deliver actionable insights
- Collaborative mindset and interest in continual learning and skill enhancement
- Ability to manage multiple priorities, seamlessly switch contexts, and adapt to evolving business needs
- Maintain focus and effectiveness in dynamic, fast-paced environments
Benefits
- medical insurance
- dental insurance
- vision insurance
- 401(k) retirement plan
- life insurance
- long-term and short-term disability insurance
- paid parking/public transportation
- paid time off
- paid sick and safe time
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningcomputer visiondata processing pipelinesobject detectionimage analysisdeep neural networksnatural language processingtime-series analysisfeature engineeringMLOps
Soft skills
communication skillsvisual storytellingcollaborative mindsetanalytical rigoradaptabilityproblem-solvingstakeholder managementprioritizationindependent driving of initiativescontinuous learning
