Top Data Science Jobs in Albuquerque, NM

Lead development of digital twin and simulation models for warehouse operations, deploy AI-driven decision systems, build forecasting and optimization models, validate experiments linking operational metrics to financial impact, and partner with engineers, operations, and external AI/academic partners to scale innovations across fulfillment networks.

Lead Data Scientist responsible for creating ML-driven risk assessments and AI workflows within a SaaS security platform, ensuring effective decision-making and system reliability.

As a Lead Data Scientist, you will design and implement scalable data pipelines and analytics capabilities while leading technical decisions across data workflows, ETL processes, and statistical modeling in the GCP environment.

Develop and prototype learning-based models using data-centric techniques; design and maintain multi-modal data and feature extraction pipelines; build auto-labeling systems; perform ETL and optimize SQL for analysis/ingestion; collaborate with data infrastructure and ML engineers to integrate workflows; write maintainable code and participate in code reviews to support scalable ML production.

The Sr. Data Scientist will design, develop, and deploy AI models and tools, mentor teams, and drive data-driven insights while collaborating with cross-functional teams.

The Senior Data Scientist leads data-driven initiatives, optimizing analytics for business decisions, mentoring staff, and ensuring data quality across healthcare projects.

The Principal Data Scientist will design, develop, and deploy machine learning models, innovating methodologies and collaborating across teams to enhance financial decision-making and risk management.

As a Principal Data Scientist, you'll design and deploy cutting-edge machine learning models to drive financial success for customers and guide technical teams.

As a Lead Data Scientist, you will shape data strategy, develop predictive models, analyze healthcare datasets, and collaborate with teams to enhance MDCalc's clinical decision tools.

As a Senior Data Scientist, you will identify business opportunities, build machine learning solutions, partner cross-functionally, and translate analyses into actionable insights.

Build, deploy, monitor, and document predictive models and analytical reports; translate findings for non-technical stakeholders; ensure model quality, fairness, and explainability; collaborate with data engineers and train staff on data literacy; support production ML infrastructure on AWS.

Lead AI/ML initiatives at Risepoint to develop predictive models for enhancing student engagement and retention, coordinating cross-functional teams to achieve measurable outcomes.

Lead development of graph-based identity resolution for CTV advertising: design models and validation, analyze large identity datasets with distributed tools, productionize data-science workflows, partner with engineering/product, and apply privacy-by-design while leveraging LLMs and AI-assisted development.

The Geospatial Scientist leads data management initiatives, oversees data governance, and ensures quality and compliance of geospatial data for DHS.

The role involves developing NLP systems for medical document analysis using advanced deep learning techniques, collaborating with domain experts, and deploying models in a healthcare setting.

Design and validate clinical and biomarker data pipelines, perform source-to-target mappings (e.g., EHR to data model), extend ontologies and vocabularies, ensure data quality, evaluate informatics tools, and support data architecture and analysis workflows for a regulatory-grade platform.

The Senior Data Scientist will analyze customer data, design experiments, build models, and support data-driven decision-making across product, marketing, and customer experience teams.

The Data Scientist will work on data analysis, visualization, and reporting, utilizing various tools to assist stakeholders' needs.

Embed with a core business unit to define problems, build metrics, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI/automation, or partnerships.

Embed with a core business area to define problems, build metrics, run analyses and experiments, produce insights and recommendations, and drive end-to-end execution to improve product, growth, AI/automation, or partnerships.

Lead product analytics to improve user growth, engagement, retention, and revenue. Design and analyze A/B and multivariate experiments, perform funnel/cohort analyses, maintain KPIs and dashboards, ensure event tracking, leverage ML and AI tools for advanced analyses, and translate insights into product recommendations across cross-functional teams.

Develop, implement, and maintain ALM and CCAR/PPNR models for balance sheet forecasting. Build customer behavior, prepayment, and deposit models; monitor performance, perform backtesting and sensitivity analysis; collaborate with Model Risk, Market Risk, Treasury, and validation teams; prepare documentation and materials for governance and senior leadership; support balance sheet optimization and regulatory initiatives.

Develop and productionize ML models for healthcare products, define KPIs, collaborate with product and customers to scope analytics, communicate results to technical and non-technical stakeholders, inform product roadmaps, and raise analytics team capabilities through code review and documentation.

As a Pricing Data Scientist, you'll develop and validate pricing models for alternative assets, collaborate with engineers, and enhance valuation accuracy through data insights.

The Data Scientist II will drive insights, develop models, and analyze product experiments to inform business decisions and improve member experiences in healthcare.