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Top Data Science Jobs
The Data Scientist will develop, improve, and manage data science and machine learning models while collaborating with R&D. Responsibilities include data manipulation, feature engineering, and model implementation. The role also involves communicating insights to stakeholders and ensuring quality control within the data team.
The Senior Data Scientist role involves identifying data sources, developing and deploying analytical models, coding, conducting data quality checks, and creating visualizations. It requires a solid understanding of the business domain, strong coding skills, and the ability to mentor junior associates. The role emphasizes delivering data-driven insights to enhance business performance and strategic decision-making.
As a Data Scientist at Horizontal Digital, you will develop algorithms and predictive models to solve business challenges for Salesforce, enhance CRM applications, and create valuable insights through data analysis and visualization. You will design data models and manage data as a product while collaborating with various teams to deliver analytics and dashboards.
The Staff Data Scientist will develop and validate predictive models using advanced machine learning techniques to facilitate fraud detection. This role involves conducting research on emerging modeling technologies, improving processes through MLOps, and collaborating with cross-functional teams to deploy models. Additionally, the role requires managing model risks and conducting analytical analyses for client inquiries.
As a Mid-Level Data Scientist at GliaCell, you will provide technical expertise for sustaining mission-critical software and systems for a U.S. Government contract, focusing on adversary defeat, mission management, and data visualization.
As a Senior Data Scientist at Independence American Insurance Company, you will research, design, and implement data models and algorithms for analyzing diverse datasets. Your role includes developing software and automated processes for data cleansing and integration, designing predictive models, and analyzing experimental results. Collaboration with product and service teams is key to identify data-driven questions and optimize outcomes.
As a Data Scientist, you will build and train AI applications, collaborate with teams globally, develop learning algorithms, and visualize data insights. A strong background in statistical modeling and experience with machine learning tools is essential.
The Staff Data Scientist will lead full-stack development of scoring services, RESTful APIs, and container-based services. Responsibilities include developing software using machine learning technologies, ensuring service reliability and security, and mentoring team members. The role requires collaboration with various teams to architect scalable solutions in a hybrid work environment.
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As a Senior Data Scientist at Coinbase, you'll analyze complex business problems, guide data metrics, and manage data visualizations. You'll also conduct rigorous experiments, collaborate with cross-functional teams to influence product decisions, and drive impactful projects in the evolving crypto landscape.
The Staff Data Scientist will develop advanced AI models focusing on large language models and Generative AI. This role involves leading data science initiatives, collaborating with interdisciplinary teams, and enhancing AI-driven interactions and personalization for impactful user experiences.
The Senior Data Scientist will develop and deploy lead scoring and recommendations models to increase sales call conversion rates, work with business stakeholders to prioritize data modeling projects, establish best practices for model performance evaluation, mentor team members on ML projects, and guide data modeling needs for machine learning systems.
As a Data Scientist with EverBright, you will develop machine learning models, analyze data quality, and optimize VPP dispatch. You will also work with distributed computing platforms and contribute code to product development teams.
The Data Scientist will focus on developing, deploying, and improving data science products within the Data Utility Office, utilizing machine learning and AI to add value to internal Federal Reserve functions. Responsibilities include maintaining operational ML/AI, enhancing data models, and collaborating with teams to create new machine learning features.
As a Staff Data Scientist, you will design and implement advanced machine learning models and data pipelines for programmatic advertising. Your role includes conducting applied research, developing evaluation frameworks, collaborating with cross-functional teams, and driving innovation to enhance performance and meet business objectives.
The Integrative Data Scientist will analyze chemical and biological data to generate hypotheses for drug discovery. Responsibilities include formulating hypotheses, developing analytic methods, recommending experiments, and effectively communicating results between experimental and computational teams.
As a Data Scientist at Slack, you will analyze data to drive business growth, present insights to senior leadership, develop predictive models, and collaborate with various teams to improve operational efficiency.
The Sr. Data Scientist will lead analytical projects focusing on predictive modeling and consumer behavior analysis within Visa. Key responsibilities include developing risk models, automating analyses, and collaborating with stakeholders. The role requires significant expertise in big data and machine learning techniques, plus the ability to present findings to non-technical audiences.
The Staff Data Scientist will lead advanced analytics initiatives for Data Solutions and Media Measurement, developing statistical models and machine learning algorithms. Responsibilities include collaborating with teams to automate measurement methodologies, mentoring other data scientists, managing projects, and communicating insights effectively.
Lead the Data Science team, developing AI models and statistical systems while collaborating with cross-functional teams. Drive research and data strategies that enhance product effectiveness and farmer profitability.
The Senior Data Scientist will design, develop, and implement data analytics solutions for agency challenges, using AI and machine learning techniques to drive risk-based decision making and ensure compliance with grant requirements. Responsibilities include stakeholder engagement, data analysis, and presenting insights.
The NFL Data Scientist will develop and improve machine learning and statistical models for Swish's sports betting products, analyze model performance, and collaborate with data engineering and product teams. Responsibilities include rigorous experimentation and documenting model development.
As a Senior Data Scientist on the Search Ranking Team, you will develop, validate, and deploy machine learning models that enhance product search relevance. Your work on machine learning and data analysis will influence customer interactions and purchasing decisions across various platforms. You'll collaborate with team members to optimize search results based on a multitude of factors, directly impacting millions of users' experiences.
The Data Scientist will enhance marketing intelligence by optimizing paid media, conducting experiments, and tracking web performance. Responsibilities include marketing analysis, KPI management, user engagement measurement, and employing research methodologies like A/B testing. They will also segment customers, create data visualizations, and present findings clearly to drive business growth.
As a Data Scientist at Coinbase, you will analyze products to provide strategic recommendations, design experiments to assess impact, and maintain key metrics. Collaboration with Product, Engineering, and Design teams is essential to influence product direction and enhance data insights.
The Sr Principal Data Scientist at Alcon will lead efforts in designing and building analytics products using AI and ML technologies to transform digital health solutions. Responsibilities include collaborating with cross-functional teams, architecting data analytics products, mentoring junior staff, and promoting data-driven decision-making practices.
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