Top Remote Data & Analytics Jobs in Philadelphia, PA

Leads international CRM decision intelligence, translating customer, campaign, and market data into strategy and next-best-action recommendations. Oversees predictive analytics, segmentation, measurement, dashboards, data quality, privacy, opportunity sizing, and AI-enabled insight generation across global markets. Partners with CRM, data, AI, digital, commercial, legal, and compliance teams to scale trustworthy personalization and analytics.

Supports enterprise decision-making through advanced analytics, reporting, data quality validation, exploratory analysis, hypothesis testing, predictive modeling, and campaign performance assessment. Collaborates with business and technology stakeholders to define data requirements, build analytical solutions, combine datasets, enforce governance standards, and deliver actionable insights. Requires independent judgment, effective communication, and the ability to manage multiple priorities and variable schedules.

Lead revenue analytics by developing business cases, dashboards, KPI frameworks, experiments, and automated analytics solutions. Partner with client success, marketplace, merchants, and cross-functional teams to evaluate performance, guide go-to-market decisions, quantify product value, and scale data-driven execution. Serve as the analytics subject matter expert while translating structured and unstructured data into actionable recommendations and compelling stakeholder narratives.

Architect scalable data models and ELT pipelines powering the data lake, analytics, AI, and machine learning initiatives. Lead enterprise data modeling, governance, observability, discoverability, and self-service analytics products. Provide technical and business leadership, partner with data scientists and stakeholders, establish engineering standards, develop data tools and frameworks, and improve data literacy. The role also involves root-cause analysis, business storytelling, mentorship, and applying AI tools to streamline data processing and democratize access to data.

Lead customer listening and Voice of Customer programs, including NPS, CSAT, CES, surveys, and interviews. Analyze qualitative and quantitative customer data to identify drivers, trends, pain points, and opportunities. Present insights to executives and cross-functional teams, facilitate action planning, and drive systemic customer experience improvements. Evaluate AI tools for sentiment analysis, theme extraction, and customer research while helping build a data-driven, customer-centric culture.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Supports analytics teams by creating reports and dashboards, conducting data extraction, cleaning, validation, and basic analysis. Documents queries and business requirements, translates business needs into specifications, supports projects under guidance, and communicates findings to technical and nontechnical stakeholders. The role also develops foundational skills in data storytelling, governed cloud data platforms, metric validation, and workload organization.

Serves as an enterprise architecture subject matter expert within a DoD environment. Supports DoD Business Enterprise Architecture initiatives, business process alignment, enterprise strategy, stakeholder analysis, requirements documentation, reporting, and project activities using MEGA HOPEX and Microsoft Office tools.

Designs and develops complex cloud-native data solutions, scalable batch and real-time pipelines, APIs, data models, and enterprise data platforms. Implements data governance, quality, lineage, security, observability, CI/CD, automated testing, and operational reporting capabilities. Collaborates with architects, product owners, analysts, governance, security, and platform teams on technology strategy and cloud modernization. Mentors engineers, leads technical design discussions, presents recommendations, and supports AI-ready data products and emerging development tools.

Leads and develops a Data Platform engineering team while owning delivery of complex data initiatives. The role establishes delivery discipline, assesses technical and implementation risks, partners cross-functionally, and drives production reliability, data quality, observability, incident management, and on-call readiness. It also guides the evolution of scalable data ingestion, transformation, lakehouse, cloud architecture, governance, and reusable platform capabilities.