Top Remote Senior Level Data Science Jobs in Philadelphia, PA

Senior Data Scientist role at Samsara focused on Data Visualization. Responsibilities include creating dashboards, setting visualization standards, and collaborating with product and engineering teams to translate business questions into quantitative artifacts.

Join Arity as a Machine Learning Scientist to work on building scalable distributed machine learning models for analyzing geospatial data and creating innovative insights. Collaborate with a cross-functional team to enhance transportation safety and efficiency through data-driven solutions.

The Senior Data Scientist at Bonterra is responsible for developing analytics and predictive models to support organizational capabilities. They will work closely with data engineers, product engineers, product managers, and other data scientists to optimize user experience and outcomes for enterprise-level software. This role involves owning predictive model requests, mentoring junior data scientists, and quantifying analytic success.

The Senior Data Scientist NLP and GenAI role involves designing and implementing NLP algorithms, language models, and collaborating with cross-functional teams to address business challenges. Responsibilities include leading analytics projects, optimizing business processes, and ensuring the ethical use of NLP technologies.

Develop and deploy advanced data science models using LLMs, GPT, and RAG. Utilize deep learning techniques to drive business growth and enhance functionality on the platform. Communicate findings to stakeholders.

A Senior Data Scientist role at PwC focusing on using technology to collect data, develop models, and provide predictions to stakeholders. Responsibilities include defining tasks, experimenting with algorithms, validating models, automating training, and communicating insights to stakeholders.

Responsible for extracting, managing, and analyzing data within Discover. Conduct research on business data, communicate findings to stakeholders, and set up efficient processes and systems for working with data. Manage and escalate risk and customer-impacting issues. Gather, structure, and analyze data from multiple sources, provide recommendations to management, and develop standard data analyses, reports, and dashboards. Coach and guide less experienced analytical professionals. Demonstrate technical knowledge in analytical tools.