Top Machine Learning Jobs in Mexico
The Staff Data Scientist will collect, analyze, and optimize big data while contributing to the organization's Big Data Strategy. Responsibilities include building predictive models, creating visualization dashboards, and collaborating with cross-functional teams to drive data-driven solutions. The role emphasizes continuous learning and innovation in data science methodologies.
The Manager of Data Science for Pricing Algorithms at CarMax will develop and optimize models that accurately value vehicles based on various market conditions. Responsibilities include analyzing data, leveraging machine learning techniques, conducting controlled experiments, and communicating insights to senior leaders.
As a Machine Learning Engineer at Kalepa, you will lead the development, deployment, and scaling of machine learning models to analyze and understand business risks using diverse data sources. The role involves collaborating with Product Management and Software Engineers to drive project direction.
The Machine Learning Engineer will frame, develop, and deploy machine learning models to analyze risk for various businesses. They will work with both structured and unstructured data to derive insights, collaborating closely with product management and software engineering teams during two-week sprints, maintaining project ownership.
The ML Research Scientist will lead research on large language model (LLM) safety, focusing on developing innovative techniques for safe, high-quality, and explainable models. Responsibilities include spearheading research, co-authoring papers, collaborating with teams, and delivering scalable algorithms.
The postdoc will support machine learning research for decision support, contributing to AI and turbulent flow simulations. Responsibilities include designing AI algorithms, implementing uncertainty quantification methods, and deploying these methods on high-performance computing systems to enhance simulations.
The Senior Data Scientist will perform data analytics using structured and unstructured data, develop metrics and reports into BI dashboards, and work closely with stakeholders to design data-driven solutions. They will also manage ongoing processes, ensure compliance, and collaborate across various functions to enhance analytics delivery infrastructure.
As a Machine Learning Engineer, you will lead the framing, development, and deployment of machine learning models at scale to assess the risk of various business classes, turning large amounts of structured and unstructured data into actionable insights. You will work collaboratively in a two-week sprint cycle with product and software engineering teams.
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As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models, analyzing both structured and unstructured data to provide insights into business risks. The role emphasizes project ownership and collaboration in a fast-paced environment, utilizing methodologies like two-week sprints.
As a Data Scientist at CoLab, you will design and deploy machine learning models, optimize features with large datasets, conduct A/B testing, and communicate insights through visualizations. Collaboration with engineering teams for model deployment and maintenance is key, along with ensuring data governance and infrastructure optimization.
The Data Science Manager will lead application development for Availity's products, focusing on statistical and machine learning solutions. Responsibilities include managing the data science development lifecycle, translating business requirements, analyzing technology trends, and coaching the analytics team.
As a Customer Business Analyst, you will analyze customer trends, monitor gross revenue retention, develop financial models, and support pricing decisions within the global customer operations team. You will provide insights for upsell and renewal strategies, create executive reports, and ensure pricing data accuracy across systems like Salesforce.
As an eDiscovery Associate at Bright Labs, you'll apply expertise in forensics, predictive analytics, and machine learning to enhance case strategies and optimize litigation profiles. Key responsibilities include designing eDiscovery workflows, identifying risks, and leveraging advanced data techniques.
Looking for a Senior AI/ML Scientist with experience in creating, optimizing, and deploying ML and NLP solutions. Responsibilities include building and deploying AI solutions for document review, organization, and Q&A processes.
As a Sr. Data Scientist, you will transform data into actionable insights, leveraging advanced machine learning and statistical techniques. Collaborate with teams to design and deploy scalable AI-driven models, solve business challenges, and improve decision-making processes.
As a Senior ML/Research Scientist at NextSense, you will develop state-of-the-art wearable neurotechnologies, conduct innovative research, and apply machine learning and signal processing techniques to analyze biosignals and develop digital biomarkers for neurological conditions. You will collaborate with a team to translate research into practical applications and engage in writing scholarly publications.
As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess business risk using diverse data sources. You will work closely with Product Management and Software Engineers, driving projects in a two-week sprint format while taking full ownership of your work.
As a Machine Learning Engineer at Kalepa, you will lead the framing, development, and scale deployment of machine learning models. You will process large datasets, transforming structured and unstructured data into insights about business risks. The role includes collaboration with Product Management and Software Engineers while working in a two-week sprint.
The Senior Data Scientist will leverage advanced analytics and machine learning to drive growth and enhance customer experience for Gap Inc's brands. Responsibilities include creating predictive models, guiding audience targeting strategies, and collaborating with various teams to ensure data quality and implement data-driven strategies.
The Principal ML Engineer will build and deploy scalable machine learning models, develop web applications for data insights, and collaborate with cross-functional teams to deliver impactful data-driven solutions. Responsibilities also include providing consulting services for data-driven decision-making.
The Data Scientist will leverage data science techniques to extract insights from customer data within the Customer Data Platform. Responsibilities include developing predictive models, implementing machine learning algorithms for personalization, collaborating with marketing and sales teams, creating visualizations, and ensuring alignment of initiatives with business objectives.
AI Scientists at HHMI develop and execute AI-based research projects aimed at biological discoveries. They lead collaborative teams, oversee projects, explore new methods, and contribute to scientific publications. They work on a range of scales, from individual projects to large initiatives, and ensure coordination across teams.
As a Manager of Data Science, you will lead a team to develop and optimize decision systems and create scalable, data-driven products that drive business outcomes. You'll manage machine learning models and statistical analysis to generate insights and enhance company processes, fostering innovation and mentoring junior team members.
The Principal Predictive Analytics Consultant leads the analytics team in designing and delivering solutions like Automated Underwriting and Risk Scoring. Responsibilities include managing complex datasets, developing predictive models, ensuring solutions meet business objectives, and presenting findings to stakeholders.
The Sr. Data Scientist will develop and improve predictive models for pricing algorithms at CarMax, focusing on feature engineering and incorporating new insights. Responsibilities include leveraging statistical and machine learning techniques, conducting controlled experiments, and communicating findings to senior leaders to drive business change.
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