Top Data & Analytics Jobs
As a Research Scientist on the Interpretability team, you will develop methods for understanding large language models through the reverse engineering of algorithms within neural networks. This involves designing and conducting robust experiments to achieve mechanistic interpretability, aimed at improving the safety and performance of AI systems.
The Senior Quantitative Analyst will develop multi-asset investment frameworks, construct portfolios, build algorithms and APIs, research forecasting methods, and mentor junior analysts, all while utilizing advanced optimization and simulation techniques.
The Data Engineer will be responsible for building data pipelines and infrastructure for ML models, analyzing data processing requirements, troubleshooting production issues, and collaborating with different teams at Stanford Health Care. Preferred skills include knowledge of multiple programming languages, resource management, and a collaborative mindset.
The Data Scientist will develop and implement AI and ML models to improve patient care and administrative services. They will collaborate with clinicians and researchers, evaluate healthcare data tools, and ensure the safe application of machine learning algorithms in clinical settings.
As a Data Scientist, you will analyze large Risk and Compliance datasets, develop and monitor machine learning models, and collaborate with team members to integrate data-driven insights into products. Your role involves understanding technical dependencies and analyzing risks and benefits of various approaches to solve problems.
The Senior Machine Learning Engineer will lead the development and deployment of machine learning models to assess business risks, utilizing both structured and unstructured data. This role involves project ownership, collaboration with product management, and working in agile sprints.
The Data Scientist I at Bank of America is responsible for analyzing large datasets to identify revenue opportunities and develop risk management strategies. The role involves collaborating with stakeholders, utilizing data analysis techniques, presenting findings, and maintaining quality work across multiple priorities while fostering a collaborative environment.
The Engineering Lead Manager, Data Science is responsible for overseeing the research, development, and implementation of ML and data science algorithms within a high-performance environment. This role requires both technical leadership and the ability to drive efficiency in global transaction processing and auction evaluations.
Featured Jobs
Join Talroo as a Principal Machine Learning Scientist to scale and expand high-value business initiatives using cutting-edge AI technologies and A/B testing. Work with a top-tier team to improve job recommendation processes and provide real, measurable revenue impact. Ideal candidate will have a passion for technology and solid background in computer science.
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As a Research Scientist, you'll conduct research to enhance productivity and the discovery experience for scientists, develop AI tools, collaborate with researchers, mentor early-career scientists, and publish your findings.
As an Applied Research Scientist, you'll conduct innovative research to enhance the productivity of scientists using AI, collaborate with the team, mentor early-career researchers, author scientific papers, share open source software, and develop relationships with academic and industry organizations.
The Head of Emerging Technology & Data Science is responsible for driving advanced technology and analytics integration within Hartford Funds. This role involves leading innovation in AI and machine learning, collaborating with stakeholders to identify solutions, and maintaining a catalog of AI solution patterns. The individual will report on progress, serve as a thought leader, and represent the company in the investment community.
As a Senior Data Scientist at Pinterest, you will leverage your expertise in quantitative modeling and experimentation to tackle complex engineering challenges, collaborating cross-functionally to provide insights that enhance product development for millions of users.
The DDF Engineering Lead will oversee a team of data engineers and DevOps engineers, driving the delivery of data products and implementing DataOps practices. Responsibilities include collaborating with cross-functional teams, optimizing data pipelines, ensuring adherence to governance policies, and promoting data quality. This role requires significant technical leadership and stakeholder engagement to maximize data utilization for business value.
As an AI Research Scientist, you will advance AI/ML algorithms for robotics, integrate solutions into robotic applications, and publish research findings. The role requires collaboration with cross-functional teams and focuses on innovation in AI technologies for autonomous robots.
Conduct research and engineering in distributed systems to develop AI solutions for autonomous driving and robotics. Collaborate with global teams and universities, integrate research findings into Bosch platforms, and contribute to strategic planning with technology insights.
The Research Scientist will conduct advanced research in reliable distributed systems using AI to enable AIoT solutions for autonomous driving and robotics. Responsibilities include collaboration with global teams, research implementation, and documentation for high-caliber publications.
As a Machine Learning Engineer at Kalepa, you will lead the framing, development, and deployment of machine learning models to assess the risk of different businesses, utilizing extensive structured and unstructured data. You will take ownership of projects, collaborate with Product Management and Software Engineers, and work in two-week sprints to deliver insights on behavior and risk.
As a Staff Machine Learning Engineer at Lily AI, you will design scalable machine learning systems, optimize deep learning models, and implement best practices in ML Ops. You'll collaborate with various teams to define the ML roadmap, improve system performance, and develop tools to enhance team productivity. The role emphasizes automating workflows and transitioning prototypes to production-ready systems.
The Data Science Manager will lead a team of data scientists, engineers, and analysts, overseeing project execution, business development, and mentoring technical staff. The role involves establishing processes for quality solutions, directing complex data science programs, and communicating with senior management.
The Senior Machine Learning Engineer will develop advanced algorithms for humanoid robotics using imitation learning and reinforcement learning. Responsibilities include designing machine learning models, optimizing training processes, and contributing to team collaborations to push the boundaries of robotics technology.
The Data Scientist II role involves applying skills in AI, machine learning, and advanced analytics to develop data-driven solutions. Responsibilities include leading analytical projects, creating scalable models, collaborating with business partners to meet objectives, and promoting data science within the company.
The Generative AI Data Scientist will develop and enhance AI solutions for telematics applications. Responsibilities include implementing generative AI models, analyzing telematics data for insights, and optimizing model performance through collaboration with cross-functional teams.
As a Data Scientist at Demandbase, you'll contribute to machine learning projects that enhance the B2B buyer journey, analyze large datasets, develop and refine models, and collaborate across teams to integrate insights into workflows. You will present findings to various stakeholders using data visualizations.
As a Senior Staff Data Scientist at Moloco, you will analyze large datasets, develop experiments, and build metrics to measure campaign performance. You'll influence R&D decisions, improve machine learning and bidding systems, and evaluate the health of the ads system, while mentoring junior data scientists.
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