Top Remote Entry Level Data & Analytics Jobs in Boston, MA

Collect, clean, validate, and analyze operational data from multiple systems to support customer reporting and performance monitoring. Process SQL-based uploads, maintain accurate datasets, identify trends and anomalies, document reporting procedures, and create standardized workflows, dashboards, and tools. The role also supports process improvement and automation initiatives while collaborating with cross-functional teams and traveling to customer sites.

Maintains and verifies client and matter data across business intake and conflicts systems. Processes engagement, waiver, closure, and name-change requests; links parties; maintains ethical walls, database alerts, and administrative files; performs data cleanup and reporting projects; supports technology testing; and communicates intake and risk-management procedures to attorneys, staff, and external parties.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Own data quality across systems by designing validation rules, reconciliation processes, profiling workflows, and quality controls. Investigate discrepancies to identify root causes, apply statistical methods to detect anomalies, evaluate machine learning model outputs, and communicate findings to technical and non-technical stakeholders. Partner with engineering, BI, and business teams to establish data quality standards, metrics, controls, and reporting practices.

Build and maintain full-stack data engineering solutions supporting BioIntelliSense’s remote patient monitoring and clinical intelligence platform. The role likely involves processing health-monitoring data, enabling analytics, and supporting reporting for clinicians, patients, and employers. Specific responsibilities and qualifications are not provided in the description.

Build and manage end-to-end marketing data platforms on Google Cloud. Responsibilities include configuring GA4 and Google Tag Manager, creating BigQuery ingestion pipelines, managing Cloud Functions, Pub/Sub, IAM, and service accounts, developing LookML semantic models and dashboards, and orchestrating ETL and reverse ETL workflows. The role also supports CDP integrations, identity resolution, audience syncing, experimentation, data quality assurance, and lifecycle marketing analytics.

Serves as the technical and client-facing link between Inca Digital’s data engine and high-stakes financial and government clients. Conducts OSINT, web scraping, enhanced due diligence, blockchain and crypto investigations; analyzes large datasets; audits and synthesizes technical findings into intelligence reports; briefs executive stakeholders; and coordinates cross-functional teams to align products with client needs.

Leads client-facing database migration and modernization engagements across AWS, relational, and NoSQL platforms. Designs migration architectures, data pipelines, ETL/ELT workflows, proof-of-concepts, and reusable technical accelerators. Facilitates executive conversations and workshops, translates complex technical solutions into business outcomes, and supports pre-sales opportunities. The role also develops GenAI-enabled migration tooling, influences senior stakeholders, and collaborates with distributed engineering, product, and data teams.

Develop and evaluate realistic Excel tasks and solutions for AI training data. Apply advanced Excel capabilities including formulas, PivotTables, data modeling, dashboards, Power Query, Power Pivot, and VBA across multiple industries and business functions. Provide written feedback, close research knowledge gaps, improve model performance, and collaborate with subject matter experts. Requires reliable weekday availability, initially 40 hours per week and 20 hours thereafter.

Analyze and manipulate large datasets supporting energy modeling and SEM programs. Review data before and after modeling, maintain standardized templates and databases, integrate data into statistical software, quality-control models and reports, and create work instructions. The role also involves automating data processing, troubleshooting Visual Basic and Excel tools, managing Smartsheet data, supporting benchmarking reports, and collaborating with internal teams and occasional clients.