Top Remote Data Analyst Jobs

The Senior Data Analyst will lead the design and implementation of machine learning models, analyze large datasets for business insights, and mentor junior team members, while collaborating with cross-functional teams.

Lead RWD analysis strategy and execution: develop technical specifications and statistical programs, perform complex observational analyses (propensity scoring, ML), validate cohorts/variables, ensure QC, collaborate cross-functionally, and communicate results to non-technical stakeholders.

The Data Product Analyst designs and manages data products for insurance domains, ensuring they meet analytical and compliance standards while collaborating with cross-functional teams.

The Senior Data Analyst will manage subscription billing analytics, optimize queries in ClickHouse, and create dashboards for stakeholders. Responsibilities include data pipeline maintenance and anomaly investigation.

The Senior Data Analyst (CX) will analyze customer support data, optimize processes using automation and AI tools, and present insights to improve customer experiences.

The Data Analyst will analyze healthcare data, create summaries for stakeholders, manage projects, and collaborate with various teams to improve processes.

The role involves developing processes for sales operations, analyzing order pipelines, managing revenue forecasting, and enhancing sales tools. Responsibilities include implementing changes for efficiency and communicating with stakeholders.

As a Data & Analytics Analyst, you'll collaborate with clients to create tailored solutions, implement prototypes, and share ideas to solve analytical challenges.

Seeking a Senior Data Analyst to transform data signals into actionable insights for advertising campaigns, leveraging skills in SQL and AI tools.

Support CBP's Advanced Trade Analytics Platform by preparing and analyzing datasets, performing ETL, validating data, developing reports and dashboards, assisting data scientists with modeling, and communicating findings to stakeholders.

Translate business and analytic requirements into secure, reliable data visualizations and solutions. Elicit requirements, build executive-level dashboards (fast, with minimal oversight), own data products, perform data profiling/wrangling, and collaborate on standardized reporting and self-service analytics while applying secure engineering practices.

The Senior Data Analyst will lead complex data analysis projects, mentor junior analysts, develop dashboards, and provide insights to drive strategic decisions. Responsibilities include troubleshooting data issues and communicating findings effectively.

As a Forward Deployed Data Analyst, you will configure and implement data systems for clients, ensuring their analytics are accurate and actionable. You'll work with teams to refine metrics and improve data processes, ensuring value from day one.

Support CDC Division of HIV Prevention by capturing program data, producing reports, monitoring fund commitments and disbursements, translating scientific evidence, and coordinating program activities to ensure data quality and project success.

Lead and coordinate large-scale SAP S/4 HANA data migration and conversion activities for Order-to-Cash processes. Create conversion specs, value maps, data models, track milestones, manage risks, run cross-functional meetings, monitor issue resolution, support testing and hyper-care, and drive documentation, reporting, and continuous improvement.

Designs and maintains operational dashboards, repeatable SQL data pulls, and analytics for claims reprocessing and payment integrity. Partners with operations and IT to translate requirements, ensure data quality and audit-ready reporting, perform ad-hoc analyses, and migrate manual extracts to governed data products. Hands-on with claims data, BI tools, and data warehouse platforms.

Own and deliver high-impact retail data products by designing and running QA, investigating and resolving complex data quality issues, improving classification and attribution, collaborating with Insights and Engineering to automate and streamline pipelines, and communicating methodology and limitations to clients and stakeholders.

Research, evaluate, and manage partnerships with data providers. Assess datasets for coverage and interoperability, support deal structuring, maintain partnership pipeline, and collaborate with product, engineering, and legal to integrate data into the platform.

Lead analytics for product or business domains by transforming data into actionable insights. Define and track KPIs, build dashboards and reports, perform EDA, cohort/funnel and A/B test analysis, validate data quality, partner with Product and Engineering, use AI tools to accelerate analysis, mentor junior analysts, and manage end-to-end analytical projects.

Lead role combining program performance management and data analytics to administer EVMS and program management tools, develop automation, perform cost/schedule analysis, mentor teams, and drive process improvements to support DoD/defense programs.

Build automated enterprise reporting across clinical, operations, claims, and risk adjustment; answer ad-hoc SQL questions; design ETL and data marts with engineering; ensure data quality and documentation; develop clinical business logic and regulatory/PACE reports; mentor analysts and set reporting standards.

The role involves delivering analytical projects in consumer credit, building machine learning models, and collaborating with clients to implement data-driven strategies.

Lead integration and data analysis efforts to connect authoritative sources to Axonius and ServiceNow CMDB. Develop 13 integrations, map and validate schemas, analyze and reconcile data discrepancies, and produce deliverables (test plans, ICDs, data management, architecture, training, security assessments). Train points-of-contact and support CMDB/security data management.

Audit and ensure quality of data labeling work for ML using human-in-the-loop processes. Provide feedback, train and support annotators, monitor workflows, identify recurring issues, and help improve guidelines and processes.

Audit and review data labeling outputs, provide actionable feedback, train and support labeling teams, monitor workflows, identify recurring issues and edge cases, participate in calibrations and stakeholder syncs, and help improve guidelines and processes in human-in-the-loop AI workflows.