The Data Scientist will design and maintain data pipelines while developing statistical models to support cross-departmental decision-making. They will also own production data systems and communicate key analytical insights to executive leadership.
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The Data Scientist will own the research and modeling roadmap for diagnostic and clinical workflows while defining rigorous frameworks for experimentation and causal evaluation. They will partner with engineering and product teams to translate complex data insights into actionable product features and business strategies.
The Data Scientist will collaborate with cross-functional teams to design, build, and operationalize predictive models to solve business challenges. They are responsible for gathering and cleaning data, performing exploratory analysis, and communicating insights to stakeholders using visualization tools.
The Data Scientist will research and experiment with multifamily datasets to identify new product features and pricing insights. They will partner with product and engineering teams to translate revenue management workflows into scalable, data-driven tools.
The Data Scientist will contribute to the development, validation, and maintenance of statistical and machine learning models for media measurement products. They will also analyze large datasets to identify trends and provide actionable insights to cross-functional teams and clients.
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Design and build algorithms to power intelligence, analytics, and automated data labeling for the Reflow platform. Collaborate with engineering and product teams to productionize models and translate complex business problems into actionable data-driven solutions.
The Data Scientist will design, implement, and deliver analytics products while building predictive models and data visualizations. They will collaborate with cross-functional teams to troubleshoot problems and ensure high-quality modeling results.
The Data Scientist will design machine learning models, perform predictive analytics, and analyze large datasets to identify trends. They will also collaborate with business stakeholders to translate data insights into actionable business decisions.
The Data Scientist will build predictive models and forecasting frameworks to analyze streaming data and audience behavior. They will also collaborate with cross-functional teams to optimize marketing campaigns and translate complex data into actionable business insights.
The Data Scientist will contribute to the development, validation, and maintenance of statistical and machine learning models for media measurement products. They will analyze large datasets to identify trends and collaborate with cross-functional teams to deliver actionable insights.
Design, train, and optimize machine learning and deep learning models for advertising and ranking systems. Collaborate with engineering and business teams to translate objectives into effective ML solutions while mentoring other data scientists.
The Data Scientist will apply advanced analytics and machine learning to support strategic decision-making across underwriting, claims, and product teams. They will also collaborate with engineering to operationalize models and integrate analytical insights into business workflows.
The Data Scientist will design and advance the AI systems powering the platform, focusing on everything from classical NLP to cutting-edge LLM architectures for tasks like intent detection and entity extraction. Key duties include designing and optimizing Retrieval-Augmented Generation (RAG) systems and implementing agentic architectures with frameworks like LangChain.
The role involves working on end-to-end classification and forecasting use cases, from data preparation and model development to evaluation and basic deployment support. Responsibilities also include building visualizations, delivering reports to stakeholders, and collaborating with engineers to move models into production.
The Data Scientist will collaborate closely with a senior research team member on cutting-edge Applied AI, infrastructure, and tooling to democratize Generative AI. Example projects include building RAG pipelines, creating Python libraries for GenAI on AWS, and implementing new neural network architectures.
The Data Scientist will leverage foundational Data Science to support children with special healthcare needs by communicating with stakeholders to translate goals into robust ML/AI models aimed at improving clinical outcomes. This involves working with cross-functional teams to define requirements, optimize data collection, build data assets, and deliver insights on business strategy and patient care.
Core responsibilities include interpreting raw data to form compelling narratives that communicate the company's story and mission, and shaping the organization's data in collaboration with Data Science, Product, and Client Services teams. This role also involves formulating, developing, and optimizing production models and augmenting the machine learning system to support advertisers in efficient media buying.
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The role involves working on AI and Machine Learning projects hosted in the Azure cloud, solving advanced ML challenges like forecasting and segmentation, and building solutions based on Large Language Models (LLMs). Responsibilities also include leading projects technically, preparing documentation, conducting training, and collaborating with clients to translate requirements into technical solutions.
The role involves using analytical and statistical approaches to solve complex business problems using large datasets, while collaborating with product managers and engineers to enhance user experience through usage analysis. Responsibilities also include conducting A/B tests, building performance dashboards, and utilizing statistical methods and machine learning for trend prediction and customer segmentation.
The job description is very brief, simply inviting candidates to join the team. Specific core responsibilities for the Data Scientist role are not detailed in the provided text.
The role involves designing, building, and deploying machine learning and generative AI solutions for real-world products, requiring hands-on work with production AI systems and collaboration with engineering and product teams. Key tasks include developing predictive and generative models, building LLM-powered features using RAG pipelines, and managing the full lifecycle of model deployment and monitoring.
The role involves designing, developing, and maintaining reproducible, production-grade machine learning models to drive core business decisions. Key tasks include building behavioral forecasting models, developing uplift models for causal inference, and scaling next-best-action recommendation systems.
The role involves designing, developing, and maintaining scalable data science services for AI/ML workflows, including implementing core capabilities like classification and prediction within containerized environments. Additionally, the individual will build and operationalize ML models for decision support and automation, ensuring model reproducibility and packaging inference services with well-documented APIs.
The Data Scientist will develop predictive models to solve critical business problems and own the development of time-series forecasts for capacity planning. They will also lead the design and analysis of A/B tests and apply advanced statistical methods to uncover insights from complex datasets.
This role will partner closely with Shopping Product teams to enhance the home discovery experience for buyers, guiding the product roadmap in this area by identifying opportunities and supporting feature testing. Responsibilities also include monitoring core metrics trends to drive timely investigations when necessary.
The Data Scientist will support the design, development, and implementation of analytical solutions to solve complex business problems. Responsibilities include data wrangling, modeling, testing, deployment, and communicating insights to stakeholders.
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As a Data Scientist, you will build production-grade ML systems that drive real-world outcomes such as energy efficiency and predictive maintenance. You will collaborate with engineers and product managers to translate raw sensor data into reliable models.
The Data Scientist will design and deliver backend services that integrate Generative AI and RAG into real-world products. Responsibilities include building scalable systems, developing AI agents, and collaborating with product and engineering teams to enhance customer experience.
As a Data Scientist, you will work on client projects and internal research initiatives, solving real-world problems and contributing to AI alignment research. You will build data-driven solutions and leverage machine learning models to deliver impactful results.
Data Scientist
PEOPLE TECHNOLOGY AND PROCESSES LLC
·
Full Time
·
26 Weeks Ago
PEOPLE TECHNOLOGY AND PROCESSES LLC
The Data Scientist will facilitate the preparation and execution of Planning, Programming, and Budgeting Committee forums and support data analytic efforts. Responsibilities also include developing topics and presentations for submission to the PPBC-G process and enhancing websites and applications for analytic efforts.
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