Top Data Science Jobs in Washington DC,
As a Senior Revenue Operations Analyst, you will oversee sales process planning and optimization, ensuring data accuracy in Salesforce and improving revenue operations. Key responsibilities include opportunity management, data analysis, and reporting, collaborating with sales and IT teams to enhance processes and outcomes.
As a Data Scientist, you will design, develop, and implement models and solutions for agency challenges, conduct data analyses, prepare and manage data, and lead teams while mentoring other scientists.
The Mid Level Energy Programs Scientist will support energy sector improvements globally, focusing on clean energy, governance, energy poverty, and security. Responsibilities include working with U.S. Federal Agencies to enhance energy services, encourage sustainable development, and respond to various agency priorities.
The Senior Level Energy Programs Scientist will support energy program requirements for a US Federal Agency, focusing on sustainable energy development, technical assistance, and the governance of energy sector improvements. This role involves addressing global energy demands and supporting international projects in various countries, with a focus on clean energy, energy poverty, and energy security.
The PPM Data Scientist/Statistician II supports a scientific agency by analyzing data related to oceans and climate conditions. Responsibilities include data mapping, ETL activities, resolving data issues, and supporting data management processes. Strong analytical and quantitative skills are essential, along with experience in federal government operations.
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The Senior Applied Analytics Analyst will provide business analytics for new product development, client consultation, and benefit plan analysis. Responsibilities include executing department-specific reporting, verifying data integrity, analyzing data sets, supporting client consultations, and leveraging statistical methods to identify solutions.
As a Data Science Analyst, you will leverage data to drive strategic decisions while developing the Narrative Analytics offering. Responsibilities include utilizing machine learning techniques, conducting data analysis, and collaborating with teams to create narrative-driven data sets that meet customer needs.
The Director of Data Science & AI will lead a team in developing and deploying advanced analytics and AI techniques. Responsibilities include innovation in AI solutions, collaboration with various teams, and effective communication of complex ideas to leadership, ensuring the impactful application of data science in the mortgage industry.
This role involves supporting a large GenAI program for the IRS by leveraging generative AI technologies to enhance tax administration. Responsibilities include cleaning and managing large datasets, developing predictive models, collaborating with teams, and creating documentation for data insights.
The Senior Data Scientist will develop, design, and maintain AI-based systems, focusing on Natural Language Processing and Machine Learning models. They will participate in code reviews and collaborate with various client delivery teams to enhance user experiences in a GenAI program for the IRS.
The Data Visualization Specialist will engage with teams to design and build accurate data visualizations from various data sources, aiding decision-making for stakeholders and development teams. Responsibilities include creating new visualizations, fixing data issues, and participating in planning meetings, all while fostering collaboration in a diverse and distributed team.
The Biosurveillance Scientist will support the DHS’s CWMD Office in analyzing and reporting biological events impacting national security. Responsibilities include open-source data collection, management of technical projects, and enhancing operational reporting through research and consulting. The role requires adaptability and strong project management skills.
The Senior Data Scientist will drive innovation in AI-driven consumer insights by developing and deploying neural networks and machine learning models to tackle predictive analytics challenges. Responsibilities include building data pipelines, ensuring model governance, identifying new machine learning applications, and collaborating with product teams while adhering to ethical principles in machine learning.
Top Companies in Washington DC, Hiring Data + Analytics Roles
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