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The Junior Data Scientist will support the Learning Technology Branch by developing tools for data management, enhancing situational awareness, and creating predictive analytics to assist in political-military decision-making processes during acute crises. The role includes prototyping user interfaces, cleaning data, recommending techniques, and keeping updated with innovations in data science and AI.
Glean is seeking a Data Scientist to collaborate with engineering, product management, and design teams. The role involves defining data assets, measuring AI product performance, identifying KPI improvement opportunities, and creating frameworks for experiment analysis and statistical modeling. The focus is on optimizing user experiences across different product modalities with a strong emphasis on product analytics.
The Manager of Data Science will lead a team of data scientists to develop and implement machine learning models that enhance subscription services and drive business growth. The role involves managing the full ML lifecycle, collaborating with engineers, providing insights from data analysis, and mentoring the team.
The Staff Data Science Engineer will spearhead data-driven innovations for online grocery delivery at Instacart, focusing on building intelligent systems, enhancing data collection methods, and developing user-friendly tools for data scientists. This role requires strategic collaboration across teams, prioritizing various data initiatives, and implementing complex technical solutions that impact multiple facets of the business.
The AHL Fellowship Program is a five-week summer opportunity for undergraduate sophomores, focusing on financial services. Fellows will gain insights from senior leaders, participate in training, and work on a curriculum-based project aimed at professional development and potential future employment with JPMorgan Chase.
The ABP Fellowship is a five-week paid summer program designed for undergraduate sophomores to explore career opportunities in financial services. Fellows will engage in learning, mentorship, and a project-based curriculum. Successful completion may lead to a 2026 Summer Internship offer.
As a Manager of Data Science, you will lead a team in developing predictive models for consumer credit risk management, leveraging technologies like Python and AWS. You'll partner with data scientists, engineers, and product managers to deploy and optimize machine learning models, translating complex data insights into business strategies.
The Director of Data Science will lead a high-performing team to implement innovative analytics approaches, focusing on machine learning and predictive modeling to optimize human resources functions. They will collaborate with various stakeholders to enhance data governance, develop data science strategies, and align HR data sources with organizational needs.
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Lead and execute data strategies across Roblox's Creator, Studio, and Engine ecosystems, focusing on enhancing tools, optimizing performance, and integrating advanced technologies like LLM and Generative AI. Collaborate with cross-functional teams to drive product innovation and improve the creator experience.
As a Manager of Data Science, you will lead a team to develop advanced machine learning solutions that address significant business challenges, create customer valuation models, and communicate effectively with stakeholders to translate business needs into data-driven strategies.
As the Director of Data Science - Model Risk at Capital One, you will lead a team utilizing various technologies to develop machine learning models and provide insights from extensive data. You will collaborate with data scientists, software engineers, and product managers to enhance decision-making processes and model management within the organization.
The Director of Data Science - Model Risk will lead a cross-functional team to develop machine learning models and insights from large datasets, focusing on risk management. Key responsibilities include collaborating with data scientists, software engineers, and product managers while leveraging innovative technologies to improve model reliability and decision-making processes.
The Manager of Data Science will lead initiatives to enhance code quality and efficiency in machine learning applications. Responsibilities include mentoring data scientists, evaluating machine learning pipelines, developing documentation, and fostering a culture of coding excellence within the Retail Bank Data Science team.
Lead a team of data scientists to solve complex business problems in financial crime compliance using AI/ML techniques, collaborating with stakeholders to drive data-led transformations and communicate solutions effectively.
The Vice President - Data Science Lead will analyze large-scale workforce data and create statistical and data science models to address employee-related business questions. Responsibilities include designing analytics models, collaborating with technology teams, communicating insights, and developing automated solutions while adhering to data protection policies.
As a Staff Data Scientist, you'll design and implement new features, mentor team members, and collaborate with engineers to create data-driven solutions. This role involves developing machine learning models, working with structured and unstructured data, and communicating insights to stakeholders while promoting best practices in data science.
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The Senior Manager of Product Data Science will lead a team of data scientists to develop data and AI products, collaborate with product managers and engineering leaders, establish a roadmap, and design experiments for product improvements and customer engagement.
As a Sr Manager of Data Science, you will lead a team to develop and execute data science projects, employing analytics to enhance customer experiences and drive product innovations in retail technology. Your role will involve collaboration with various stakeholders, establishing product visions, and analyzing data to generate actionable insights.
The successful candidate will teach courses in mathematics, statistics, or data science while engaging in interdisciplinary research initiatives and collaborating with faculty across various fields. They will incorporate modern methods like machine learning in their teaching and research.
The Lead Applied Research Scientist - Responsible AI will develop strategies for creating cutting-edge generative AI capabilities while addressing ethical risks. They will lead projects focusing on AI trust and safety, and work collaboratively with cross-functional teams to ensure responsible AI practices are implemented throughout the development process.
The AI Solution Manager role involves partnering with customers to identify enterprise-level problems solvable by ML applications, leading cross-functional teams to develop AI solutions, and collaborating with sales to expand accounts. The role requires excellent problem-solving, communication skills, and a strong understanding of business operations.
As a Data Science Associate, you will develop AI-driven models for cost insights, create data pipelines and dashboards using Snowflake, Python, and Tableau, and contribute to automation and optimization of business processes. You will also monitor AI model performance to enhance decision-making and support agile data-driven teams.
As an AI Tutor at Alignerr, you will enhance AI models' understanding of data science through teaching, evaluation, and resistance testing. Your responsibilities will include applying statistical methods, guiding machine learning applications, and fostering data ethics in AI. The role requires both technical expertise and a commitment to exploring AI advancements.
The Lead Data Scientist for People & Culture develops predictive models, conducts statistical analysis, and creates data visualizations to help inform organizational decisions. This role collaborates with various stakeholders to enhance HR processes using data-driven insights and stays updated on advancements in data science and analytics.
The Senior Data Scientist will work with health and care data to provide insights and recommendations, maintaining algorithms, integrating new datasets, and creating data visualizations. Collaboration with operations, sales, and product teams is essential to address business needs through data-driven solutions.
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