Jobs at YipitData

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.

The Data Product Analyst will own Signals data products, work with AI and Data Engineering, ensure data quality, conduct analyses, and shape product improvements through client feedback.

Own product positioning and go-to-market strategy for YipitData’s AI and big data products serving public investors. Define customer segments and messaging, lead product launches, conduct competitive intelligence, support pricing and packaging, and create sales enablement materials. Partner with Product, Revenue, and Insights teams to shape the roadmap and drive adoption. Establish GTM success metrics, monitor performance, and improve strategies across data feeds, software, and AI-powered investor solutions.

Commercial Counsel will partner with commercial teams to draft, negotiate, and execute business contracts, including NDAs, while advising on legal and commercial issues. The role will improve contract processes, forms, and management systems; facilitate internal reviews; develop contracting frameworks; and recommend legal solutions aligned with business needs. This remote-friendly position requires strong judgment, communication, attention to detail, and the ability to work independently in a fast-changing technology and data-products environment.

Lead and transform YipitData’s global talent acquisition function, managing approximately seven recruiting professionals. Assess and redesign recruiting processes, establish scalable operating rhythms and metrics, advise senior leaders, improve sourcing and talent pipelines, oversee executive searches, and optimize the ATS, automation, and AI-enabled recruiting technology ecosystem. Drive stakeholder alignment, change adoption, hiring quality, speed, consistency, and continuous improvement.

Lead end-to-end development of AI-enabled, full‑stack products and production AI Agent systems. Own architecture, APIs, observability, and deployments; collaborate with product and stakeholders; balance rapid prototyping with scalable engineering; integrate LLMs and agent loops; mentor others and ensure reliability, performance, and customer-focused UX.

The Director of Strategic Data Partnerships will identify and execute exclusive data partnerships, engaging with executives to build alignment and negotiate complex agreements. This role focuses on strategic judgment and ongoing relationship management to drive product development and growth.

Manage and grow enterprise Technology/Cloud accounts by owning renewals, driving upsells and cross-sells, building executive relationships, coordinating with Solutions/Product teams, maintaining pipeline/forecast in CRM, and meeting revenue and retention targets.

As a Sales Executive, manage the entire sales process, qualify leads, and close opportunities, focusing on enterprise subscription sales with a strong emphasis on client relationships.

The Product Manager will define and scale a quant platform for alternative datasets, collaborate with teams to develop product specifications, conduct customer research, and manage go-to-market strategies.

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.

Target and break into large enterprise accounts (>$100M software spend) using outbound prospecting (cold calls, emails, LinkedIn) to generate meetings with procurement leaders. Use modern sales tools, collaborate with sales leadership and enablement, refine messaging, and develop toward full end-to-end sales responsibility.

Own global tax strategy, compliance, preparation, filings, tax planning, transfer pricing, and risk management. The role oversees federal, state, local, and international tax matters; manages tax calendars, nexus, sales taxability, provisions, reconciliations, and regulatory inquiries; and partners with external advisors, auditors, treasury, accounting, and internal stakeholders. The position serves as the organization’s primary tax contact and drives tax process improvements.

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.

Lead AI product strategy for investor workflows, building AI-native products (agents, copilots, MCPs, APIs) that turn proprietary data into reliable, production-grade investor tools. Partner with customers, engineering, design, and research to run experiments, define quality/trust frameworks, and ship 0→1 products that automate and augment investment decision-making.

Outbound-focused SDR responsible for prospecting Finance, Operations, and IT leaders via cold calls, emails, and LinkedIn to generate meetings. Use sales tools (CRM, calling/email platforms), refine messaging, and work with sales leadership to progress toward full-cycle sales.

Owner of high-impact data products for corporate clients: design and run QA processes, investigate and resolve complex data quality issues, collaborate with Insights and Engineering, communicate with stakeholders, and identify opportunities to automate and improve workflows while mentoring peers.

Lead a hands-on data engineering team to build and scale production data pipelines, datasets, and observability for alternative-data products. Drive architecture, data modeling, QA, and AI-ready dataset design while coaching engineers, partnering with product and research, and owning operational excellence across Databricks, Airflow, SQL, and PySpark.

Own and QA high-impact retail data products: design and run QA, investigate and resolve complex data quality issues, collaborate with Insights and Engineering, improve automation and product reliability, and communicate methodology and limitations to clients.

Build and own end-to-end, production-grade full‑stack features across backend, frontend, data pipelines, and infrastructure. Collaborate with stakeholders to translate business problems into shipped software, drive cross-team initiatives, and improve tooling and code quality. Use AI coding tools daily to accelerate development and maintain reliability for customer-facing products.