Top Remote Data Science Jobs in Detroit, MI

The Senior Healthcare Data Scientist at Garner will be responsible for building data-driven algorithms to power care navigation, doctor ranking, and healthcare-related financial products by applying medical and healthcare economics understanding. The ideal candidate will have 2-5 years of professional experience in healthcare and/or data science fields, formal training in data science and a branch of healthcare, experience with Python and SQL, and a willingness to contribute to improving the U.S. healthcare system.

Partner with business leaders to address challenges using predictive analytics, improve data quality, align analysis with strategic goals, and train statistical and machine learning models. Spot trends, publish insights at scale, and mentor team members.

Lead the development of statistical models and data analysis to solve complex business challenges, drive revenue growth, and present data findings to executives. Collaborate with various teams and provide data-driven solutions to business leaders. Minimum qualifications include 7+ years of experience as a data scientist and 5+ years of experience with Python for model development.

The Principal Data Scientist will be the primary analytics partner to the Community & Learning team at Atlassian. They will influence strategy and important decisions, build measurement frameworks, lead high-impact projects, promote a measurement culture, and foster a world-class Data Science culture.

Chainlink Labs is seeking a Research Engineer with expertise in applied cryptography, distributed systems, and security to define research agendas and drive projects impacting the success of Chainlink's vision. The role involves conceptualizing and designing next-generation systems, pursuing fundamental research, and enhancing company visibility within the scientific community.

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.

Design, develop, and program methods, processes, and systems to analyze big data sources and generate actionable insights. Collaborate with product and service teams to identify questions and issues for data analysis and experiments. Develop software programs, algorithms, and automated processes to cleanse and evaluate large datasets. Communicate insights and findings to stakeholders.