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.

Supports healthcare data analytics and research projects by evaluating diverse datasets, developing statistical models, validating and cross-referencing data, analyzing care and outcome patterns, and communicating findings to nontechnical stakeholders and clients. The role includes learning healthcare data types, SAS programming, research design methods, and quality improvement analytics while collaborating across multiple teams and managing concurrent projects.

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.

Develops and maintains Power BI dashboards and data models, defines KPIs with stakeholders, validates data accuracy, and collaborates with Data Engineering on optimized analytical models. The role documents data lineage and reporting assumptions, supports self-service BI through communications and training, and automates manual reporting processes. It requires SQL, Power BI, DAX, Power Query, data modeling, and data warehouse knowledge, plus strong communication and cross-functional collaboration skills.

Supports the Mortgage Lending Division by producing and maintaining routine reports, dashboards, data extracts, and basic analyses. Validates data accuracy, automates reporting where appropriate, documents procedures, investigates trends and audit issues, and responds to operational reporting needs. The role involves learning internal systems, metrics, and business processes while collaborating with stakeholders. Candidates should have basic Excel and data visualization skills, foundational SQL knowledge, strong analytical abilities, and zero to two years of relevant experience.

Supports the Mortgage Lending Division by producing and maintaining routine reports, dashboards, data extracts, and ad-hoc analyses. Validates data accuracy, documents reporting procedures, investigates trends and audit issues, and collaborates with business teams to understand performance metrics and reporting needs. The role requires basic Excel and data visualization skills, foundational SQL knowledge, attention to detail, and a willingness to learn internal systems and processes.

Designs and maintains scalable batch and streaming data pipelines and datasets in Databricks using Python, Spark, and SQL. Supports SQL Server, SSIS, SSRS, Azure, data warehousing, reporting, analytics, and AI/ML workloads. Responsibilities include optimizing performance and reliability, implementing data quality controls, integrating enterprise data sources, modernizing platforms, and partnering with business and IT teams to deliver scalable data solutions.

Analyze and tune sanctions, fraud, and AML models; evaluate performance, reduce false positives, develop features and datasets, automate analysis, troubleshoot data issues, and communicate findings to technical, compliance, regulatory, and senior management stakeholders.

Lead the design and development of Azure-based big data solutions, including batch and real-time ETL/ELT pipelines, data architecture, ingestion, curation, warehousing, and storage. Build solutions using Azure Data Factory, Databricks, Synapse, Spark, Python, SQL, and related Azure services. Support Salesforce migration and integration while applying strong RDBMS, data management, and big data design expertise.