Top Data Science Jobs in Albuquerque, NM

As a Staff Data Scientist for Forecasting, you will develop forecasting algorithms, create data pipelines, mentor team members, and operationalize models for business needs.

As a Staff Data Scientist, you will develop data-driven fraud prevention solutions using Generative AI, design scalable ML pipelines, and mentor junior data scientists while collaborating across teams to improve analytics and decision-making.

Build and productionize AI/ML solutions on a modern AWS federal data platform: implement RAG/vector stores, develop and validate models and pipelines, automate via Airflow/Glue/Spark, integrate with ETL metadata, ensure security/compliance, write tests and documentation, and support agile delivery.

The Senior Data Scientist will lead innovative data science efforts, leveraging advanced analytics, visualization, and insights from complex datasets to boost productivity.

As a Staff Data Scientist, you will lead initiatives to build and optimize machine learning models, collaborate across departments, and solve complex business problems using data.

The Data Scientist role involves designing and deploying machine learning systems, prototyping AI agents, collaborating with product teams, and addressing business problems. Responsibilities include model building, data analysis, client collaboration, and contributing to AI tooling.

Lead and manage data science teams to build models and drive business solutions; oversee compliance analytics and ensure data quality.

The Senior ML Data Scientist will develop machine learning models to detect fraud, manage the data science lifecycle, and collaborate with teams on strategies.

Analyze ACH transaction data to enhance payment decisioning performance. Identify trends, evaluate data impact, and optimize risk strategies using Python and SQL in a fintech environment.

Build and own measurement systems, MMM, incrementality, and experimentation frameworks to quantify marketing incrementality, optimize budget allocation, forecast LTV/CAC, and operationalize production-grade models and metrics to drive growth, retention, and long-term enterprise value.

The role involves leveraging advanced analytics and machine learning to assess and mitigate credit and fraud risks, developing scalable modeling solutions while collaborating with stakeholders.

The role involves designing, building, and deploying machine learning models, collaborating with teams to address business problems, and mentoring other data scientists.

Lead design and ownership of advanced fraud detection models and monitoring. Apply adversarial threat modeling to select architectures (tree-based, deep, graph), debug production failures, run experiments, mentor engineers, and build AI-assisted workflows that scale domain expertise while resisting manipulation.

The role involves preparing traffic data, developing and deploying machine learning models on Google Vertex AI, and collaborating with teams to improve project workflows.

The Data Scientist II will oversee data management, design study protocols, train staff, lead report development, and manage client activities using project frameworks.

As a Data Scientist II, you will analyze complex data, develop statistical models, and create data visualizations to support internal clients and enhance analytics capabilities. You will collaborate with technical leads and stakeholders, ensuring data quality and accuracy in deliverables.

As a Data Scientist, you will develop advanced fraud detection models, collaborate with teams, analyze data for insights, optimize models, and ensure compliance with data privacy.

As a Business Intelligence Data Scientist, you will develop dashboards, build statistical models, and analyze product features to enhance user insights.

Partner with product engineering to design and analyze experiments, apply causal reasoning and statistical modeling to marketplace data, and drive data-informed product decisions across the engineering org.

The Staff Data Scientist will oversee Foodsmart's member growth analytics, focusing on marketing and product funnel optimization, experimentation, attribution modeling, and enhancing self-service analytic tools while collaborating closely with leadership and cross-functional teams.

The Data Scientist II will work with sports tracking data to build models and analyses for NHL and NBA organizations, focusing on data transformation and metrics development.

The Applied Data Scientist III will develop scalable AI solutions, analyze data, and translate technical concepts for stakeholders while advocating for AI adoption.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Develop, deploy, and operationalize analytical and ML/AI models for cybersecurity use cases. Collaborate with product and engineering teams to enable and migrate production workflows, work with databases and data architectures, create visualizations and reports, adopt new cloud orchestration and data virtualization technologies, and mentor junior cyber data scientists.

Conduct original economic research using Stripe transaction and public datasets; apply econometric and causal methods; build reproducible data pipelines; create economic indicators; translate findings for product, policy, and external audiences; publish and present research; collaborate cross-functionally and with external partners.