This role sits at the intersection of SRE, DevOps, and data, helping to improve reliability, observability, and operational maturity of data platforms, Kubernetes-based deployment systems, internal applications, and cloud environments.
Compensation
In the U.S., the standard base pay range for this role is $102,800.00 - $190,204.00 Annual.
Responsibilities
Monitor service health, respond to alerts, and participate in incident response for cloud, Kubernetes, application, and data platform environments.
Support the reliability of internal applications, APIs, workers, streaming consumers, event-driven services, and deployment workflows used by data engineering and business teams.
Build and maintain dashboards, alerting, runbooks, and operational documentation that improve detection and recovery speed.
Improve observability for Databricks environments, including job health, Spark streaming workloads, structured streaming metrics, cluster behavior, failures, latency, throughput, and cost signals.
Join an international, cross-functional team to build AI-driven solutions for background screening, splitting time between delivering new products and supporting production ML workloads.
Responsibilities
Work within a Scrum team on new products and initiatives, from design through delivery.
Provide dedicated support for existing production AI/ML workloads, ensuring reliability, performance, and continuity.
Build secure, well-optimized solutions using modern AI tooling.
Develop and productionize ML models, and design end-to-end testing strategies to hold delivered solutions to a high quality bar.
Deliver API integrations and data pipelines, optimizing for latency, throughput, and cost.
Senior Data Scientist who designs, develops, and implements machine learning models, AI systems, and statistical modeling to generate actionable insights for business problems and product development.
Compensation
Pay Range: $108,960.00 - $163,440.00 Annual
Responsibilities
Designs, develops, programs and implements Machine Learning Models (Clustering, Classification or Regressions models).
Performs Statistical Modelling and Measurements by applying data engineering, feature engineering, statistical methods, ML modelling and AI techniques.
Develops and applies novel models on customer data to identify areas to increase profits and reduce losses.
Partners with experimentalists to translate models into testable hypotheses.
Lead the company’s commercial data initiatives and operations, ensuring data integrity, scalability, and compliance across commercial functions.
Compensation
The base compensation range for this role is $165-190K.
Responsibilities
Guides the design and ongoing optimization of scalable commercial data architecture
Translates commercial priorities into a practical data roadmap
Leads MDM initiatives, ensuring HCP, HCO, payer, and master data are accurate and governed
Partners with Sales Operations/Business Intelligence and the managed service provider to define and maintain data definitions, business rules, stewardship processes, and data-quality controls
Establishes data governance policies and compliance frameworks to maintain data integrity and security (HIPAA, GDPR)
Requirements
Bachelor’s or Master’s degree in Computer Science, Data Analytics, Business Intelligence, or a related field
Lead the AI roadmap and product strategy for business applications across multiple enterprise domains, driving innovation and impact in a cybersecurity context.
Compensation
The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.
Responsibilities
Own and prioritize an AI-powered roadmap tailored to business applications across Sales, Licensing, Finance, Support, Customer Success, and BI & Data Analytics.
Partner with business leaders to identify bottlenecks and apply AI/Agentic workflows to streamline critical enterprise journeys.
Build and iterate on functional prototypes using AI-native tools and low-code platforms to validate AI agent interactions with enterprise APIs.
Define error budgets, accuracy guardrails, and compliance standards for AI outputs in business-critical systems.
Create and version-control Golden Sets to grade AI model performance in real-world business scenarios.
The Senior Data Architect is responsible for designing, implementing, and managing the data architecture that supports Valley Health System (VHS) analytics and business intelligence initiatives within the healthcare sector.
Compensation
$52.00 - $81.32
Responsibilities
Develops and maintains robust data architectures (cloud and on-prem) that support analytics, reporting, and operational workflows and integrate EHR/EMR systems (e.g., Epic, Cerner), claims data, HL7/FHIR interfaces, and patient-reported outcomes.
Creates and manages conceptual, logical, and physical data models that reflect business processes and analytical needs.
Designs and oversees ETL pipelines and data integration strategies to ensure efficient, accurate, and timely data flow from diverse sources.
Defines and enforces data standards, metadata management, and data quality frameworks to ensure trust in enterprise data assets.
Implements frameworks to ensure HIPAA compliance, PHI protection, and adherence to ONC/CMS interoperability rules.
Design and build data ingestion and transformation pipelines, manage data storage and processing layers, and provide technical leadership to data engineers.
Responsibilities
Design and build data ingestion and transformation pipelines
Manage data storage and processing layers
Ensure data performance, reliability, and quality
Implement data engineering best practices and standards
Provide technical leadership and mentoring to data engineers
Lead AI product strategy and roadmap for business applications across multiple enterprise domains.
Compensation
The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.
Responsibilities
Own and prioritize an AI-powered roadmap tailored to business applications across Sales, Licensing/Entitlements, Finance, Support, Customer Success, or BI & Data Analytics
Partner with business leaders to identify manual bottlenecks and apply AI/Agentic workflows to streamline critical enterprise journeys
Use AI-native tools to build and iterate on functional prototypes that validate how AI agents interact with standard and proprietary enterprise APIs
Define error budgets, accuracy guardrails, and compliance standards for AI outputs within business-critical systems
Create and version-control “Golden Sets”—definitive datasets derived from internal enterprise data, logs, financial records, and customer telemetry
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