Garantizar la medición óptima y eficiente de los riesgos estructurales y de liquidez, mejorando inputs, parámetros y modelos analíticos.
Responsibilities
Garantizar la medición óptima y eficiente de los riesgos estructurales y de liquidez, mejorando inputs, parámetros y modelos analíticos
Calibrar la adecuada valuación y proyección de métricas de riesgos en la integración de nuevos productos financieros a las herramientas y reporting
Proporcionar criterios de negocio necesarios para la medición adecuada de riesgos en proyectos estratégicos del banco
Implantar nuevas métricas, parámetros y reporting ejecutivo de riesgos, alineándose a criterios corporativos globales para robustecer la toma de decisiones de la Alta Dirección
Generar pruebas de resistencia inversa, evaluar impactos en modelos y desagregar nuevos factores para anticipar impactos adversos y escenarios de estrés
Assist in preparing and curating datasets for AI/ML model training, support testing and validation of AI-driven tools, work on data preparation and visualization for business insights, and contribute to process improvement projects within IT operations.
Responsibilities
Assist in preparing and curating datasets for AI/ML model training
Support testing and validation of AI-driven tools and solutions
Collaborate with global and regional teams to document AI workflows and best practices
Work on data preparation, cleansing, and visualization for business insights
Support development of dashboards and reports using BD-approved tools
Requirements
Currently pursuing a degree in Computer Science, Information Technology, Data Science, or related field
Join the engineering team that builds the data products, integrations, and AI-enabled tools the rest of Amplitude runs on. This role will specifically support Marketing and Go-to-Market. You’ll partner with Marketing Operations, Revenue Operations, Sales, and Analytics to build reliable data pipelines, trusted business models, and reusable semantic and context layers.
The Staff Data Engineer is a critical member of Hershey's Enterprise Data & Analytics organization, responsible for delivering a seamless, governed, and scalable AI platform experience across the enterprise. This role bridges AI engineering, platform engineering, and product thinking to ensure AI and data tools are easy to discover, adopt, and operationalize.
Responsibilities
Own and evolve the AI platform roadmap across Databricks, Azure ML, and related technologies
Pilot, evaluate, and operationalize new AI platform capabilities
Build and maintain governed, scalable AI infrastructure including compute environments, deployment pipelines, monitoring solutions, feature stores, and AI services
Design and implement "paved road" solutions that provide secure, compliant, and repeatable workflows for AI and machine learning development
Embed AI Trust, Risk, and Security Management (AI TRiSM) practices into platform processes
As an early team member, you will get a chance to shape both the foundations of the product, backend architecture, and team culture. Our client will measure your success by your ability to ship fast, learn quickly, and contribute to our culture of continuous improvement.
Compensation
Competitive equity as a founding employee of a startup funded by top tier investors
Responsibilities
Design and build server-side Human L1 and blockchain architecture (using Golang, Cosmos SDK, AWS, Azure)
Write technical documentation
Manage the server-side technical team
Develop and manage well-functioning decentralized databases
Support the day-to-day operation, security and reliability of our enterprise network, administering wired, wireless and perimeter infrastructure across multiple locations.
Compensation
Competitive Salary: Industry-standard salaries with opportunities for performance-based bonuses
Responsibilities
Administer and support the security, performance and availability of switching, routing, wireless and firewall infrastructure using industry-leading tools like Cisco, Palo Alto and Aruba (or similar)
Manage secure remote access, including site-to-site and client-based VPN connectivity
Monitor network health and performance, respond to alerts, and resolve issues before they impact users
Troubleshoot network incidents, escalate complex issues to senior engineers, and document root cause and resolution
Implement network changes, upgrades and expansions in line with change management practices and with minimal disruption to operations
As a Senior (Lead) Software Engineer supporting Wellmark’s Data Quality Management (DQM) initiative, you will help maintain and enhance an AWS-based platform that delivers automated data quality scoring across enterprise data sources.
Responsibilities
Support or lead the design and development of efficient, cost-effective solutions using modern cloud technologies, infrastructure as code, and event-driven architectures to solve complex data reliability challenges and support enterprise decision-making.
Build and enhance platform features spanning infrastructure, application code, and CI/CD pipelines.
Support AWS CDK deployments across multiple environments.
Implement data quality checks and validation logic across diverse data sources.
Monitor, debug, and improve workflow performance and reliability.
Requirements
Bachelor’s degree in Computer Science, MIS, or related field of study
Build data-driven applications, workflows, and solutions using the Palantir Foundry platform, translating complex data into scalable solutions that support mission and business objectives.
Compensation
The projected compensation range for this position is $69,400.00 to $158,000.00 (annualized USD).
Responsibilities
Develop and maintain solutions using the Palantir Foundry platform
Build and maintain data pipelines using Foundry Pipeline Builder and related tools
Develop applications, workflows, and data products within the Foundry ecosystem
Integrate, transform, validate, and manage data from multiple sources
Work with Foundry Ontology and data models to support analytical and operational use cases
Help modernize how a U.S. Army's program captures, preserves, and reuses data generated during high-value system test events. Design and implement dependable data storage and processing capabilities that replace manual file transfers and fragmented local copies with secure, organized, searchable repositories.
Compensation
The projected compensation range for this position is $62,000.00 to $141,000.00 (annualized USD).
Responsibilities
Automate data ingestion, quality validation, relevance-based curation, indexing, version tracking, and backup and recovery.
Preserve source provenance and test-event and software-version context.
Build a foundation for future automated dashboards and controlled data access by authorized stakeholders.
We are looking for an Analytics Engineering Intern who is eager to learn and passionate about transforming information into actionable insights. This role is ideal for students with curiosity for programming, process automation, and building scalable analytical solutions.
Responsibilities
Support the development of automated data workflows and reporting processes
Assist in building scripts and tools using Python to improve operational efficiency
Work with structured and unstructured data to support analytics and automation initiatives
Collaborate on process optimization and automation projects across teams
We offer competitive pay and benefits packages that reflect our commitment to the health and well-being of our Ampliteers.
Responsibilities
Build and operate production data pipelines using Fivetran, dbt, and Snowflake, integrating CRM, marketing automation, advertising, product usage, and other business data.
Create trusted Marketing and GTM data products for campaign performance, funnel conversion, attribution, account engagement, intent scoring, and pipeline analysis.
Build and maintain semantic layers that define shared business entities, relationships, dimensions, and metrics so dashboards, analysts, and AI tools use consistent definitions.
Develop context layers for AI-enabled analytics, capturing business terminology, metric descriptions, synonyms, approved joins, business rules, and verified queries that help tools interpret data accurately.
Partner directly with business stakeholders to understand workflows, clarify ambiguous requirements, validate assumptions, and translate business problems into practical technical solutions.
Requirements
Nice to have: Marketing attribution
Nice to have: Campaign influence
Nice to have: Lifecycle marketing
Nice to have: Account scoring
Nice to have: Warehouse-to-business-system activation
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