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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.
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.
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As a Senior Data Scientist, you'll partner with cross-functional teams to deliver AI-powered products that enhance customer experiences. Your responsibilities include leveraging advanced technologies to analyze vast data, building machine learning models, and operationalizing them for scalable production systems. You'll also act as an expert in NLP and LLMs to drive innovation and communicate complex ideas effectively to stakeholders.
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 a Data Scientist at Square, you will apply statistical and machine learning techniques to empower decision-making for the unified point of sale product, collaborate with teams for data-driven strategies, and develop resources for data accessibility.
As a Data Scientist, you will develop complex models for object detection and analyze various data sets to support national security. You will work in a collaborative R&D environment, integrating data from diverse sources, training models, and providing insights to decision-makers.
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.
As a Senior Data Scientist at Capital One, you will develop and implement AI and machine learning models for customer-facing applications. Your role includes partnering with engineering teams, leveraging various technologies to analyze large data sets, and operationalizing scalable AI solutions. You will also mentor junior team members and translate complex findings into actionable business insights.
As a Data Scientist, you will lead the integration of AI within data collection applications at Morningstar. Responsibilities include automating data collection processes, collaborating with analysts, designing ML/AI solutions, and improving workflows. The role involves strong development skills and requires knowledge in NLP and AI technologies.
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.
As a Data Scientist II at WHOOP, you will develop algorithms utilizing wearable sensor data to generate insights on health and performance. Collaboration with MLOps, product managers, and other scientists is essential to design, train, and deploy machine learning models that analyze sleep and training information.
As a Senior Data Scientist at Capital One, you will partner with cross-functional teams to deliver AI-powered solutions, leveraging advanced technologies for insights in large data sets. You will build and fine-tune NLP models for customer-facing applications, ensuring scalability and operational effectiveness in a customer-centric environment.
As a Data Scientist II at Chewy, you will develop and implement models to solve complex supply chain issues using optimization and machine learning. Your role includes creating data science frameworks and improving existing processes through advanced analytics while collaborating across various teams.
As a Data Scientist at Twitch, you will enhance product performance measurement, lead analytics methods, and support community safety. Responsibilities include conducting A/B tests, producing reports, and translating product questions into metrics. You'll collaborate closely with product teams to improve community interactions, influence product design, and ensure data-driven decision-making.
The Data Science Lead is responsible for defining and building data assets to track performance metrics for AI-powered products. They will work with engineering, product management, and design to improve key performance indicators and develop quantitative methodologies for performance analysis. The role focuses on user experience and cross-functional collaboration to enhance Glean's AI products.
The Data Scientist will develop analytic solutions for TransUnion's clients in credit, fraud, insurance, and marketing applications. Responsibilities include leading analytic engagements, creating predictive models, and providing insights through data extraction and analysis. The role involves collaboration with cross-functional teams and requires effective communication skills.
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