Top Entry Level Data & Analytics Jobs in Boston, MA

Designs conceptual, logical, and physical data models for R&D research and clinical domains. Translates scientific and business requirements into reusable, scalable, AI-ready data structures that support analytics, machine learning, data integration, and standardized workflows. Partners with domain experts, data engineers, architects, data scientists, and governance teams to apply enterprise standards, schemas, ontologies, metadata, quality rules, and lineage. Promotes shared data assets and ensures models are implementable, interoperable, and aligned with evolving R&D needs.

Participate in a rotational analyst development program focused on using data and technology to analyze performance trends, identify business opportunities, and support insurance operations. Complete training, mentorship, and rotational assignments while developing strategic, technical, analytical, communication, and business skills. Use tools such as Excel, SQL, Python, R, SAS, Snowflake, Power BI, and emerging AI technologies to generate business insights.

Supports retail space planning through data analytics, performance reporting, and store layout optimization. Creates and validates Power BI dashboards and reporting tools, analyzes space productivity, maps data, and identifies actionable opportunities. Collaborates with Space Planning and Commercial Solutions teams while maintaining merchandising standards. The co-op combines business analytics, retail strategy, database concepts, data visualization, and emerging AI tools in a hybrid environment.

Analyze and visualize large customer datasets, build production-grade data models and scalable data products, automate manual analytical workflows, and create AI-assisted, conversational, and self-service analytics experiences. Translate ambiguous stakeholder needs into actionable solutions while collaborating across teams and experimenting with generative AI and modern data technologies.

Analyze data and develop semantic models for certified data products covering rebates, sales-to-GMR, and inventory. Build and rationalize Power BI dashboards, collaborate with Finance and business stakeholders on requirements and user acceptance testing, and consolidate reports into certified data products. The role requires expertise in Power BI semantic modeling, DAX, advanced SQL, Athena, Redshift Spectrum, dimensional modeling, and star schemas.

Conduct prospect research on individuals, corporations, and foundations to identify and qualify donors. Develop prospect profiles, synthesize information, maintain accurate CRM data, support fundraiser preparation, and improve research processes and data quality. Collaborate with Advancement staff and research leadership to provide timely insights that inform donor engagement and fundraising strategy.

Build and support Databricks Lakehouse pipelines, curated datasets, and analytics-ready data models using Spark, Delta Lake, Python, and SQL. Integrate Databricks with SQL Server, SaaS, and enterprise systems; implement data quality, governance, security, and monitoring practices; optimize Spark workloads; and support CI/CD and platform administration. Collaborate with analysts, data scientists, stakeholders, and Data Enterprise teams to modernize legacy data processes and deliver reliable production data products.

Own and improve federal data quality, fulfill customer data requests, build tailored data feeds and trackers, and identify patterns for customer insights and marketing thought leadership. The analyst will conduct QA across personnel, organizational, and program data, collaborate with data, product, and engineering teams, and translate data gaps into platform improvements. The role requires basic SQL, analytical writing, attention to detail, and comfort working across competing priorities.

Build and scale data insights capabilities, write SQL queries in Snowflake, transform data with Python, and create dashboards in Qlik Sense and Tableau. Support data governance, preprocessing pipelines, predictive modeling, documentation, version control, and automated data workflows. Collaborate with Data Engineering teams to deliver real-time insights for robotics and supply chain automation projects.

Two-year early talent program developing data engineering professionals. Responsibilities include building and maintaining scalable data pipelines, integrating and transforming data, developing data models, implementing quality checks, and supporting data governance. The role uses SQL, Python, cloud platforms, and modern data engineering tools while collaborating with engineers, analysts, and business partners on production data solutions.