Top Data & Analytics Jobs
The Staff Data Scientist will lead the development of generative AI models for e-commerce data, optimize advertising campaigns using advanced machine learning techniques, conduct experiments to validate model performance, and collaborate with leadership to enhance the advertising ecosystem.
Conduct world-class research on data analytics and contribute to the long-term research agenda in large-scale data analytics and machine learning. Develop AI/Machine learning models to detect credit card information attacks. Collaborate with product stakeholders to formulate and solve complex technical data problems.
As a Machine Learning Engineer, you will be responsible for leading the development and deployment of machine learning models to evaluate business risks. You will analyze structured and unstructured data sources to provide insights while managing projects within a two-week sprint framework, collaborating closely with product and software teams.
Lead a team of data scientists in delivering advanced statistical techniques and machine learning solutions for underwriting and operations. Collaborate with partners to drive analytics into products, enhancing decision-making and improving business outcomes. Present insights to executives and influence strategic decisions, while also guiding team development and recruitment efforts.
As a Staff Data Scientist, you will leverage advanced statistical techniques and machine learning to build models solving key business problems and improving distributor intelligence. Your role involves leading analytical projects, communicating insights to stakeholders, and mentoring junior team members in data science best practices.
In this role, you will lead and support the design and development of enterprise data products, manage multiple data engineering teams, influence data strategy, and mentor professionals in the data engineering community. You will leverage your technical expertise to transform data into actionable insights, overseeing the operational processes and ensuring efficiency and innovation.
As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to evaluate business risks using various data sources. You will own projects, driving their direction while collaborating with Product Management and Software Engineers in a sprint-based environment.
The Research Scientist will apply scientific expertise to advance Google DeepMind's mission, focusing on developing methods for teaching large language models to graphically explain concepts, creating evaluations for performance, exploring multimodal AI across various domains, and contributing to training and publishing research on the Gemini project.
Featured Jobs
As a Senior Data Scientist at Rocket Money, you'll build machine learning-driven features in collaboration with engineering, product, and design teams. You'll also optimize product feedback loops, develop automation for budgeting tools, construct customer segmentation models, run experiments to gauge impact, and ensure accuracy in transaction categorization systems. You'll lead projects, drive strategy, and focus on enhancing customers' financial experiences.
As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess business risk, utilizing both structured and unstructured data. You will have full ownership of projects and collaborate closely with Product Management and Software Engineers in a sprint environment.
The Senior Machine Learning Engineer will work on developing AI-powered software, fine-tuning large language models, conducting multimodal product research, and ensuring model alignment to improve user experience at Scribe.
The Machine Learning Engineer at Scribe will design and implement advanced AI techniques, optimize model performance, and create benchmarking infrastructure. Responsibilities include translating AI innovations into features, working on memory management, and collaborating with engineering teams to enhance model quality.
The Machine Learning Engineer will work on AI-powered software development, focusing on multimodal capabilities including vision and audio. Responsibilities include designing data pipelines for model training, improving model performance through experimentation, and collaborating with various teams.
As the Lead Data Scientist, you will establish a data science practice, collaborate with various teams to optimize systems, leverage data for strategic decisions, and utilize advanced analytics techniques to derive insights that drive business outcomes.
The Senior Machine Learning Engineer will lead the development and deployment of machine learning models to analyze business risks using various data sources. Responsible for transforming large datasets into actionable insights, this role requires collaboration with product managers and software engineers during two-week sprints.
The Data Scientist will design and implement advanced machine learning models for real-time anomaly detection, automate data discovery from a global honeypot network, and enhance product features through AI/ML techniques. Collaboration with cross-functional teams and direct customer engagement will be essential.
As a Senior Machine Learning Engineer at Enigma, you will develop scalable ML systems, enhance entity resolution algorithms, and improve machine learning infrastructure, directly impacting business decisions for customers. You will collaborate with data scientists and engineers to innovate and maintain high-performance systems.
As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to analyze business risks using varied data sources. You'll manage projects with autonomy while collaborating with Product Management and Software Engineers in a two-week sprint cycle.
Lead the framing, development, and deployment at scale of machine learning models to assess business risk. Collaborate with teams to create insights from structured and unstructured data through a project-driven approach.
The Senior Machine Learning Engineer will lead the development and deployment of machine learning models to assess business risks using structured and unstructured data. This role involves ownership of projects with a collaborative approach alongside Product Management and Software Engineers in a sprint environment.
As a Senior Machine Learning Engineer at Kalepa, you will lead the development and deployment of machine learning models to assess business risks using diverse data sources. You will take ownership of projects, working in sprints with product and software teams to deliver insights and solutions.
As a Machine Learning Engineer, you will lead the development and deployment of machine learning models, transforming large amounts of structured and unstructured data into insights about risk for various businesses. You will work closely with Product Management and Software Engineers in an agile environment.
As a Senior Machine Learning Engineer at Kalepa, you will lead the development of innovative AI solutions for the insurance sector, utilizing your expertise to improve underwriter decision-making processes and drive significant business outcomes. You will collaborate closely with cross-functional teams to enhance the AI Copilot platform.
The Head of Portfolio Risk Analytics will lead the team in developing and overseeing the portfolio risk analytics and monitoring frameworks, focusing on risk assessment, performance analysis, and compliance with regulations in consumer finance. Responsibilities include designing risk appetite frameworks, collaborating across functions, and implementing stress testing and sensitivity analysis.
As Head of Data Science, you will lead all aspects of data science including statistical methods and data analytics. You will oversee a team of data scientists, manage large complex datasets, and collaborate with product managers and engineering. Your role will enhance data-driven insights to inform decisions and drive product improvements.
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