Top Data & Analytics Jobs

Responsible for validating market risk models and ensuring their accuracy. Engage with various stakeholders, communicate findings, and maintain model integrity while leveraging innovative analytical technologies.

Lead CX data intelligence initiatives using SQL, dashboards, analytical models, and AI/LLM techniques. Analyze customer journeys, operational metrics, churn risks, and retention indicators; develop insight agents and self-service reporting; define CX health metrics; and translate findings into strategic recommendations, process improvements, and experiments. Partner with operations, support, product, data, and engineering teams while maintaining data quality, governance, and documentation.

Design and maintain Python-based analytics frameworks for KYC quality assurance testing, statistical sampling, validation, and workflow automation. Integrate data from internal systems and APIs, apply statistical and machine learning techniques, identify control gaps, and improve testing efficiency. Document methodologies, assumptions, controls, and limitations for audit and regulatory review. Partner with risk, compliance, operations, and quality assurance stakeholders while communicating analytical findings and methodology decisions clearly.

Own pricing, yield, monetization, retention, and churn analytics for a B2B marketplace. Build supplier yield scores, pricing models, dashboards, predictive churn models, cohort analyses, and A/B tests. Partner with product, operations, engineering, sales, finance, and customer success leaders to translate marketplace data into revenue and retention improvements. Develop production machine-learning models and communicate insights to technical and non-technical stakeholders.

Own supplier-side pricing, yield, monetization, retention, and churn analytics for a B2B marketplace. Build predictive models, dashboards, data models, pricing frameworks, cohort analyses, and A/B tests. Partner with product, operations, engineering, sales, finance, and customer success leaders to identify revenue opportunities, optimize advertising and incentive programs, improve supplier retention, and translate complex marketplace dynamics into actionable business decisions.

Leads data analytics and data quality for Airbus’s Mobile final assembly facility. Manages the local data portfolio, defines data products and standards, drives data lifecycle improvements, and conducts advanced analyses using AI, machine learning, and predictive models. Translates findings into business insights, establishes KPIs, mentors analysts, supports internal tool development, and coordinates operational recovery plans. The role requires collaboration across manufacturing, process improvement, and leadership teams.

Lead enterprise and mission data architecture, modernization, integration, governance, and lifecycle strategy for cyber mission data. Design data models, pipelines, APIs, schemas, metadata frameworks, and quality controls while ensuring scalability, security, interoperability, and compliance. Provide technical leadership, architecture roadmaps, customer advising, mentoring, and cross-functional coordination across engineering, cybersecurity, infrastructure, and government teams. Support analytics, machine learning, and AI initiatives in classified environments.

Leads enterprise data, analytics, business intelligence, and AI strategy across healthcare payer functions. Partners with executives to prioritize analytics initiatives, build reporting and predictive insight capabilities, establish data governance and accountability, and drive measurable business outcomes. Oversees cross-functional teams, enterprise application development, Azure architecture, quality automation, DevOps, and intelligent automation while engaging C-suite and board stakeholders.

Designs and maintains scalable data pipelines and architectures for operational, intelligence, and mission data. Aggregates, cleans, transforms, and analyzes structured and unstructured datasets using Python, Maven Smart System, Palantir, Power BI, and AI-enabled tools. Develops dashboards, data models, metrics, reports, and decision-support products for C-UAS operations and acquisition efforts. Requires collaboration with technical and mission stakeholders, strong data governance practices, executive communication skills, and an active TS/SCI clearance.

The Director of Business Development will define, negotiate, and secure partnerships to expand adMarketplace's search and performance advertising across various platforms while ensuring alignment with company goals and operational integration.

Lead enterprise dashboard architecture and administration supporting Department of State operations. Develop executive reporting, operational monitoring, financial, quality, capacity, disaster recovery, and predictive analytics dashboards. Integrate Power BI with enterprise monitoring platforms including Splunk, ServiceNow, Oracle Enterprise Manager, AppDynamics, and Zabbix. Direct distributed visualization initiatives, supervise technical teams, and deliver analytics for large-scale IT infrastructure and mission operations.

Develops BI models, dashboards, reports, predictive analyses, and visualizations for Navy leadership assessment programs. Analyzes large datasets, identifies trends, supports executive decision-making, maintains data systems, prepares quarterly performance reports, and coordinates with stakeholders. The role also supervises an administrative assistant and may moderate milestone interviews.

Performs advanced data analysis, modeling, visualization, and predictive analytics for client and federal applications. Designs and automates HR performance dashboards, queries relational databases, develops transformation scripts, supports data governance and migration, and recommends measurable process improvements. Serves as a subject matter expert, mentors team members, communicates findings to technical and executive stakeholders, and supports classified national-security-related work.

Ten-week summer internship focused on analytics and business transformation. Interns will analyze data, create insights and recommendations, support process improvement, explore AI-enabled tools, and contribute to data-driven decision-making. The role includes cross-functional collaboration, professional development, and a capstone project. Interns must work full-time in a hybrid setting and relocate to Canonsburg, Pennsylvania, or Houston, Texas.

Ensures healthcare data is accurate, consistent, secure, and compliant. Responsibilities include requirements gathering, SQL-based data preparation, audits, data quality analysis, dashboards, KPI development, discrepancy resolution, statistical modeling, and testing. The role also develops and deploys machine learning and LLM solutions, RAG systems, AI assistants, chatbots, and automation for data quality initiatives, while supporting deployment, documentation, and training.

Designs, builds, deploys, and maintains scalable cloud-native data platforms and pipelines using AWS. Supports cloud migration, data science, AI/ML, and business intelligence initiatives by organizing structured and unstructured data. Responsibilities include database architecture, data acquisition and preparation, software development, platform modernization, analytics architecture evaluation, and cross-functional team leadership. Requires TS/SCI clearance with polygraph and substantial all-source analysis experience.

Develop and deploy containerized data applications and pipelines, including Kubernetes deployments, monitoring, optimization, and AI-powered features using LLMs. Collaborate with data scientists on data architectures and tools, troubleshoot pipeline issues, and build Streamlit prototypes. The role also requires staying current with AI, data engineering, and cloud computing practices.

Lead the enterprise data architecture roadmap and Snowflake-based data platform supporting commercial, medical, finance, R&D, quality, and corporate functions. Oversee data modeling, integration, ETL/ELT, governance, master data management, data quality, reporting, analytics, and AI-ready data products. Provide technical leadership, review designs and code, manage vendors and implementation partners, establish standards, and mentor technical staff while enabling commercial launch readiness and scalable enterprise reporting.

Lead automation of billing, journal entries, reconciliations, and recurring accounting reports. Design and maintain workflows connecting Accounting with other teams, analyze accounting data, build dashboards, and apply ML for forecasting and anomaly detection. Partner with IT and Accounting leadership, document controls, train staff, and drive automation projects from identification through implementation.

Develop and implement software solutions for automated trading systems, working with quantitative researchers on complex financial challenges.

Design, develop, and deploy software solutions for automated trading systems while collaborating with researchers on technology priorities.

As a PhD intern, you'll design, develop, and deploy software solutions for automated trading, collaborating with the Quantitative Research team.

Design, develop, and maintain scalable data pipelines, models, databases, and data infrastructure using ETL and big-data technologies. Cleanse, integrate, and validate large datasets; implement data governance; troubleshoot complex data issues; and collaborate with analysts, scientists, and stakeholders. Develop and enhance software supporting mission requirements, maintain application databases, and coordinate hardware-software integration. The role requires onsite work in Arlington, Virginia, an active Secret clearance, and U.S. citizenship.

Build, deploy, and maintain scalable data pipelines and platforms for mission-driven projects. Validate and normalize datasets, develop schemas, implement ETL workflows, and create monitoring dashboards and metrics. Collaborate with AI/ML engineers, cloud architects, and technical leaders to support governed, high-quality data flows and reliable model performance. Improve pipeline performance and support data engineering for operational, research, and enterprise systems.

Build and maintain scalable data pipelines and platforms using SQL, Java, or Python. Acquire, tag, integrate, and process structured, semi-structured, and unstructured data. Apply machine learning models for classification, use BigID and AWS, and collaborate with analysts, engineers, developers, and data consumers in an agile environment. Guide analytical exploration, data examination, platform design, deployment, and maintenance for mission-driven client projects.