Top Entry Level Data & Analytics Jobs in Boston, MA

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

This co-op develops analytical solutions for fulfillment performance reporting. Responsibilities include understanding fulfillment processes, consulting on data pipelines, developing data models and dashboards, analyzing trends, and providing insights and recommendations. The role collaborates with product managers, visualization analysts, data scientists, IT, technical teams, and fulfillment operations.

Develop market intelligence, forecasting, statistical models, scenario analyses, and automated reporting for supply chain decisions. Integrate internal and external datasets using Python, R, SQL, and other tools; build dashboards; support data governance; and translate analytical findings into recommendations for procurement, planning, and executive stakeholders.

The AI Analyst Co-op will use Python, HTML, SQL, APIs, and AI tools to generate scalable insights for go-to-market teams. Responsibilities include personalizing BDR outreach by buyer persona, distributing market insights across sales, marketing, and partner resources, and collaborating with Platform Advisory. The role requires strong analytical skills, attention to detail, problem-solving persistence, and an understanding of technology’s role in improving operational efficiency.

Supports the development and maintenance of SQL and Python data pipelines, data models, semantic layers, dashboards, and reports. Performs data wrangling and preprocessing, translates business requirements into data solutions, and contributes to data governance, security, and quality assurance. Collaborates with cross-functional teams supporting marketing, engineering, product development, supply chain, finance, business analytics, and AI initiatives.

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.

Supports enterprise applications, ERP administration, reporting, dashboards, business intelligence, SQL development, data validation, integrations, and institutional reporting. Troubleshoots system and data issues, assists end users, supports upgrades and testing, and collaborates with campus departments to deliver technology and analytics solutions while protecting institutional data.

Build and scale programmable data infrastructure supporting Vesalius Therapeutics’ human cellular biology platform. The role contributes to large-scale genetics, genomics, stem cell, cellular phenotyping, and artificial intelligence initiatives designed to uncover causal biology and identify therapeutic intervention points.

Designs and develops SQL Server databases, including tables, views, procedures, functions, triggers, constraints, and secure code. Creates SSRS reports, SSIS packages, SSAS cubes, and data warehouses. Supports application development, database migrations, performance and concurrency issues, and backend requirements gathering.

Conduct quantitative research across systematic investment strategies, analyzing large datasets, portfolio risks, signals, and fund outcomes. Develop analytics, KPIs, reporting mechanisms, and tools used by portfolio managers and researchers. Partner with quantitative researchers, traders, technologists, and portfolio managers to uncover insights and improve decision-making. Apply statistical techniques, programming, risk management, and modern AI tooling to solve complex problems.