Top Data Science Jobs in Pittsburgh, PA

As a Data Scientist II, you will analyze large healthcare datasets, build and optimize machine learning models, and develop algorithms for workflow optimization. You'll collaborate with engineers and product managers, communicate insights through visualizations, and contribute to innovative solutions that enhance operational intelligence in healthcare revenue cycle management.

The Applied Scientist will leverage advancements in AI/ML, particularly Large Language Models and Computer Vision, to enhance legal and financial tech solutions. Key responsibilities include finetuning and deploying state-of-the-art models, building ETL pipelines, and collaborating with cross-functional teams to improve AI quality in production systems.

The Senior Data Scientist will lead data analysis and machine learning efforts to extract insights from complex datasets, drive product enhancements, and influence strategic decision-making. Responsibilities include statistical modeling, data mastery, and mentorship within a cross-functional team to deliver machine learning solutions.

The Vice President of Data Science Research will lead the research organization focusing on innovative quantitative methods for liquid biopsy cancer screening, drive the research roadmap, and transition new concepts into product development while maintaining reproducible research standards.

As an Applied Scientist, you will drive the development of Reinforcement Learning models, collaborating with interdisciplinary teams to optimize models that provide actionable insights. You'll implement innovative algorithms and communicate complex technical concepts effectively to various stakeholders.

Conduct experimental studies in natural language processing and machine learning, develop dark web monitoring tools, help transition research models to production, and publish findings in top conferences. Collaborate with teammates and propose innovative ML models to enhance products.

In this role, you will collaborate with stakeholders to leverage data for insights and systems improvement, stay updated on data science techniques, design effective experiments, and work on machine learning algorithms. You will also interact with data engineers to develop robust data pipelines and create tools that facilitate data access and visualization.