Jobs at Datalign Advisory

Lead product-focused data science and machine learning initiatives, including exploratory analysis, production model development, evaluation frameworks, generative AI, graph-based machine learning, recommendation systems, and personalization. Collaborate with engineering, product, and business teams to deliver high-impact solutions, influence strategy, and communicate insights to technical and non-technical stakeholders. The hybrid role requires four days per week in the Greater Boston area.

Support marketing and communications through podcast and video production, social media management, content writing, PR, SEO, analytics, and experimentation with AI and emerging tools. Responsibilities include researching topics, creating multimedia content, managing publishing calendars, tracking engagement and website performance, supporting press and company announcements, and developing new content ideas. The role is part-time, unpaid, and requires working in the Cambridge office three days per week.

Own full-cycle hunting sales to wealth management firms: build pipeline, run discovery and demos, negotiate multi-stakeholder deals, and close net-new partnerships. Maintain forecasting and CRM hygiene, collaborate with customer success and product teams, represent the company at industry events, and contribute sales playbooks and field insights.

Lead advisor-facing revenue growth and retention by managing relationships, onboarding partners, optimizing campaigns with data-driven insights, coordinating cross-functional teams, overseeing operations, forecasting revenue, and mentoring staff.

Lead full-stack development for an AWS-based product: design and implement backend, data, and web UI; integrate external APIs and AI/ML features; collaborate cross-functionally; improve architecture and engineering practices; mentor teammates and deliver high-quality, production-ready code.

Design and implement pixel-perfect, high-performance web applications from wireframes to production. Collaborate with designers, PMs, and engineers, iterate on architecture and best practices, explore AI/ML integrations, and contribute to a collaborative engineering culture.

Own Halo end-to-end: define roadmap, shape the AI-native consumer experience, coordinate advisor handoffs, and work with engineering and data science to ship multi-agent, compliance-grade AI features. Measure success across a coupled consumer-advisor product, prioritize ruthlessly with limited resources, and embed SEC-compliant traceability into product decisions.