Top Data & Analytics Jobs
As a Senior Data Scientist, you will leverage your expertise in machine learning and statistical analysis to develop algorithms and models that optimize marketing campaigns and improve customer loyalty. You will collaborate with cross-functional teams to design and implement data-driven solutions, analyze large datasets, conduct A/B testing, and mentor junior team members.
The Principal Data Scientist will lead the implementation of AI solutions, focusing on generative AI to address complex business problems. Responsibilities include mentoring others, developing predictive models, ensuring data quality, and collaborating on product innovations to deliver value to customers.
The Data Science Senior Manager will lead the Lingo Data Science team, focusing on building next-generation Biowearables. Responsibilities include developing machine learning models, analyzing biological data, discovering trends in large data sets, conducting advanced statistical analyses, and designing signal processing algorithms.
As a Senior Data Scientist on the Search Ranking Team, you will analyze large datasets, develop and deploy machine learning models, and work on optimizing product search rankings using algorithms. You will contribute to solving complex problems in e-commerce, focusing on machine learning applications in areas like NLP, computer vision, and predictive modeling.
The Sr. Manager, Data Science will lead projects focused on optimizing Walmart’s supply chain strategies using advanced analytics and data modeling. Responsibilities include project management, data analysis, and the development of metrics and dashboards, with a goal of enhancing customer experience and operational efficiency.
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.
Featured Jobs
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 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.
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.
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.
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.
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.
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