Top Remote Data Analyst Jobs

Perform data exploration and analysis on large structured and unstructured datasets using SQL and Python. Clean and process data, build dashboards and reports with Power BI and Tableau, consult with stakeholders to gather requirements, and communicate findings to end users. Work in a hybrid Arlington, VA environment supporting federal clients.

Analyze large structured, semi-structured, and unstructured datasets using SQL and Python; clean and process data; build dashboards and reports with Power BI and Tableau; consult technical and non-technical stakeholders; communicate analysis and deliverables to end users on federal government projects. Must possess IRS Public Trust clearance.

Analyze large structured and unstructured datasets using SQL and Python; clean and process data; build dashboards and reports with Power BI/Tableau; consult stakeholders and communicate findings to end users.

Analyze large structured and unstructured datasets using SQL and Python, clean and process data, build dashboards in Power BI/Tableau, consult with stakeholders, and communicate findings to deliver analytic solutions for federal clients.

Consult with stakeholders to explore and analyze large structured, semi-structured, and unstructured datasets using SQL and Python; clean, process, and manage data; build and deploy dashboards and reports (Power BI, Tableau); communicate findings to end users; collaborate with cross-functional teams to translate requirements into analytic solutions.

Perform data exploration and analysis on large structured and unstructured datasets using SQL and Python; build and deploy dashboards in Power BI/Tableau; consult with stakeholders, communicate findings, and collaborate with data scientists and engineers to deliver analytic solutions for federal clients.

Join a cross-functional team to explore and analyze large structured and unstructured datasets using SQL and Python, build and deploy dashboards (Power BI, Tableau), consult with stakeholders, and communicate analytic results and reports to end users for federal government clients.

Administers Workday and multi-platform HR security, including role-based access, security configuration, access reviews, governance, audit support, and remediation. Evaluates routine and elevated access requests, enforces least-privilege standards, analyzes security and audit trends, maintains governance documentation, and recommends policy and process improvements. Collaborates with HR, IT, Legal, Compliance, and business stakeholders while protecting confidential employee data.

Support Product, Marketing, and Operations with operational reporting, ad-hoc analysis, and dashboarding. Build and maintain Tableau dashboards, write SQL and Databricks data marts, automate recurring reports with Python (pandas), standardize metrics, and improve reporting reliability while collaborating cross-functionally.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

Collect and analyze data to assess change management and training effectiveness; implement audits; create assessment and trend reports; develop surveys and trainings; lead interviews and focus groups; track corrective actions and timelines; collaborate across departments to recommend and support performance improvements.

Own high-impact data products, ingestion pipelines, and granular data feeds end to end. Analyze massive datasets to answer client and stakeholder questions, ensure data accuracy, and derive actionable insights. Improve products and pipelines by developing methodologies, scaling third-party datasets, and creating data modules. The role requires clear communication, attention to detail, methodical problem solving, prioritization, experimentation, and strong ownership. Training includes SQL, PySpark, Python fundamentals, and internal tools.

The role involves improving transaction monitoring rules, analyzing risk patterns, and building dashboards for compliance while collaborating with investigations and compliance leadership.

Support development and maintenance of SQL-based data pipelines and analytics workflows. Assist data standardization, build and optimize data models, dashboards, and reports. Perform ad-hoc analyses, monitor data quality, implement validation logic, and collaborate on cross-functional data and risk projects under mentorship.

Design and execute clinical evidence studies by developing dbt/SQL data models, automation pipelines, and reports. Integrate and de-identify clinical data across marts, build analysis-ready datasets, maintain code quality, validate outputs, and create visualizations and KPIs to support oncology-focused research and clinical decision-making.

Analyze complex financial and business data to guide planning, forecasting, investment decisions, and strategic growth. Partner with FP&A, Accounting, RevOps, Product, Marketing, Data Engineering, and analytics teams; automate recurring workflows; build self-service dashboards and data assets; improve analytics infrastructure; and communicate actionable insights to technical and non-technical stakeholders.

Support solution architecture by analyzing current-state processes, data flows, interfaces, and reporting needs; produce data mappings, conceptual/logical models, ER summaries, interface inventories, and stakeholder-ready documentation to inform modernization, integration, governance, and release readiness across vendors and Scrum teams.

Lead ownership of client billing data and infrastructure for Finance: run reconciliations, investigate billing issues, build BI dashboards, automate workflows with SQL/Snowflake, monitor revenue leakage, and support Billing 2.0 UAT while training Finance on reporting and Looker standards.

Updates machine learning training and test datasets, refines annotation guidelines, initiates model training, and evaluates model performance. The role annotates synthetic text and image data, conducts manual quality analysis, identifies error patterns, reports anomalies, and produces findings on utterance quality, LLM evaluation, ASR bugs, and customer pain points. It also applies basic NLP and linguistic knowledge to ensure data accuracy and consistency.

Leads analysis, mining, modeling, and visualization of large-scale transactional, operational, and customer data. Partners with compliance teams to prioritize analytical use cases, support regulatory requirements, improve business efficiency, and translate complex findings into actionable recommendations. Oversees multidisciplinary analysts, manages stakeholder data requests, assesses business changes, and develops analytical systems using machine learning, big data technologies, and visualization tools.

Supports a Department of Defense project assessing service members’ fitness for duty and eligibility for disability separation or retirement. Analyzes systems and business data, identifies data frameworks, supervises personnel, and integrates system-level data requirements and architectures into enterprise architectures compliant with DoD regulations.

Build and maintain Power BI reporting products, integrate and validate institutional data, conduct applied quantitative and qualitative research, deliver analyses and visualizations, manage projects and reporting standards, and support cross-organization analytics and stakeholder decision-making.

Own finance, accounting, and revenue operations data pipelines; develop revenue forecasts; conduct analysis; and build scalable SQL solutions, dashboards, and reports. Partner with executives and cross-functional stakeholders to translate complex financial data into accurate insights and recommendations. Maintain rigorous data validation, documentation, QA, and process improvements while managing competing priorities.

The Senior Marketing & Data Analyst will lead complex analytics projects, perform data analysis and reporting, ensure data integrity, and provide actionable insights based on market data to optimize business processes and inform decision-making.

Lead strategic analytics and partner with senior leadership to drive growth, margin, and retention initiatives. Build interactive reporting (Python/Streamlit, BigQuery-connected Google Sheets), perform deep EDA in Jupyter, model and clean data with SQL and dbt, integrate secure AI-assisted tools and automation, ensure analytical quality, and translate insights into measurable business outcomes.