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Top Senior Level Data & Analytics Jobs in Washington DC,
The Senior Data Scientist will lead quantitative analyses to guide strategic business decisions for Thumbtack's Commercial Strategy team. Responsibilities include designing A/B tests, measuring project impacts, tracking KPIs, and collaborating with various teams to present insights. This role is crucial in shaping business strategy and ensuring data-driven decision-making.
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.
The role requires leading the Credit and Data Science functions for Empower's international operations, developing risk models and credit policies, and launching innovative products to improve customer financial outcomes. The candidate will lead teams to analyze consumer behaviors and tailor solutions for different markets, contributing to business growth in Latin America and South East Asia.
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As the Director of Data Science & AI, you will lead a team to develop AI and ML solutions that align with the business strategy. Responsibilities include overseeing the ML workflow, collaborating with Product and Engineering, and managing a high-performance team to drive customer-centric analysis and strategic initiatives.
As an AI Scientist, you will develop and implement deep learning methods for chemistry, contributing to drug discovery efforts. You will work collaboratively with experts in AI, biology, and chemistry, while driving innovative research and advancing state-of-the-art AI models for molecular modeling.
The Data Analyst II at Ardent will utilize expertise in quantitative and qualitative analysis, workforce and financial modeling, and advanced data analytics to support recruitment and retention initiatives. Responsibilities include integrating data sets, building analytical models, designing dashboards for data reporting, and conducting analyses to inform decision-making processes.
The Database Administrator will manage and optimize geospatial databases, collaborate with GIS and application developers, monitor database security, and assist with database design and development for enhancements. Responsibilities also include data conversion procedures and documenting database management methodologies.
The Database Administrator will manage geospatial data repositories, ensuring secure storage and accessibility. Responsibilities include integrating geospatial databases with governmental data sources, conducting data analysis, modeling, mapping, forecasting, and report development to support energy and technology research for clients like the DOE.
The Quantitative Analyst role involves conducting statistical and data-driven analyses to evaluate workforce trends and policy impacts, especially in the energy sector. The analyst will support policy analysis initiatives and provide data tracking tools support as part of a broader effort to aid the Department of Energy and related clients.
As a Senior Data Engineer, you will create and maintain data pipelines, manage data mapping among sources, administer cloud and server services, and provide infrastructure services for big data and cross-domain data transfers.
The Database Administrator III role focuses on supporting and maintaining TNS's diverse databases, including Oracle, MongoDB, MariaDB, and SQL Server. Responsibilities include providing technical support, performing database administration tasks, ensuring data consistency and security, and overseeing database upgrades and migrations. The role requires strong SQL skills and cloud database management experience.
The Director of Data Science & AI will lead a team in producing advanced analytics and AI solutions, support strategy implementation through data mining and predictive modeling, and ensure effective communication of complex data insights. Responsibilities include driving AI advancements, collaboration with product teams, and applying innovative data science practices to enhance business applications.
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