Data Scientist

Data Scientist

Location: Eagan, MN (Onsite)

Responsibilities

Lead the development and implementation of machine learning models to solve complex business problems and enhance decision-making processes.

Oversee the application of statistical techniques and exploratory data analysis to extract meaningful insights from large datasets.

Provide expertise in Azure Open AI Service and Cloud AutoML to optimize and automate data-driven processes.

Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows.

Utilize Airflow for orchestrating complex data workflows and ensuring seamless data pipeline operations.

Develop and maintain knowledge graphs to improve data accessibility and enhance search engine optimization.

Implement MLOps practices to streamline the deployment and monitoring of machine learning models in production.

Apply deep learning techniques using PyTorch and TensorFlow to advance the company’s AI capabilities.

Conduct natural language processing and dialogflow projects to enhance customer interactions and service delivery.

Use OpenCV for computer vision tasks that contribute to innovative product development.

Engage in continuous learning and application of the latest advancements in artificial intelligence and machine learning.

Ensure the ethical use of AI technologies and contribute to the company’s commitment to responsible AI practices.

Drive the adoption of AI and machine learning across the organization to foster a culture of innovation.

Collaborate with stakeholders to identify opportunities for AI-driven improvements and efficiencies.

Qualifications

Possess a strong foundation in Statistics and experience with R Statistical Package and Python.

Demonstrate proficiency in Azure Open AI Service and Cloud AutoML for scalable AI solutions.

Exhibit expertise in machine learning frameworks such as PyTorch and TensorFlow.

Have experience with natural language processing and dialogflow for enhanced communication systems.

Show capability in using OpenCV for computer vision applications.

Understand the principles of MLOps for effective model deployment and management.

Be knowledgeable in search engine optimization techniques to improve data discoverability.