Top Tech Jobs & Startup Jobs in Boston, MA

The SpendHound Partnerships Manager will manage and grow relationships with outsourced finance partners, drive sales through these partnerships, and enhance partner engagement and performance metrics.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.

The Senior Recruiter will lead high-impact recruiting efforts for the GTM organization, focusing on strategic searches across Sales, Marketing, Customer Success, and Strategy. Responsibilities include managing the full recruiting cycle, developing talent pipelines, enhancing candidate experience, and utilizing ATS systems effectively.

The Senior Recruiter will manage full-cycle recruiting focused on senior leadership roles, develop talent pipelines, and enhance candidate experience while utilizing metrics for continuous improvement.

The Client Strategy Manager will manage client relationships, develop commercial strategies, and ensure client success through proactive engagement and support. This role includes account management, upselling, and enhancing client engagement with the firm's analytics services.

The Associate Director, Solutions will lead a client-facing team at YipitData, responsible for delivering bespoke analysis and data products, managing client experiences, and leveraging AI for operational efficiency.

Design end-to-end UX for an AI-powered B2B data product. Translate complex AI and data concepts into intuitive, trustworthy interfaces; conduct user research; define workflows; collaborate with Product, Engineering, and Data Science; contribute to design systems and maintain design quality through launches.

Own the conversion of raw alternative datasets into scalable, AI-ready data products. Define methodologies, metric definitions, and guardrails for AI-driven insights. Partner with engineering, product, and customers to expand use cases, ensure data quality, validate changes, and manage incidents to deliver reliable, explainable data products at scale.

Own and deliver high-impact retail data products by designing and running QA, investigating and resolving complex data quality issues, improving classification and attribution, collaborating with Insights and Engineering to automate and streamline pipelines, and communicating methodology and limitations to clients and stakeholders.

Lead a global, hands-on data engineering team building large-scale Databricks/PySpark pipelines, production datasets, customer-facing data feeds, AI-ready analytical datasets, and data quality/observability systems. Partner cross-functionally, use AI coding tools to accelerate delivery, and ensure operational excellence, reliability, and documentation for investor-facing products.