Top Fintech Jobs in Boston, MA

Manage a portfolio of stabilized LIHTC/affordable housing investments, monitor asset performance, analyze financials and partnership documents, identify risks, recommend and execute remediation, review and underwrite GP consent requests, oversee third-party vendors, and coach junior team members while ensuring compliance and reporting to senior management.

The Business Systems Analyst will analyze business processes, develop technical solutions, and guide technology decisions in investment management applications.

The Investment Accounting Manager oversees the integrity of accounting data for Investment Controllership, analyzes financial data across companies, and collaborates with teams to improve processes and controls.

Manage and scale Toast Capital loan financing: build financial models, produce ABS-style reporting, negotiate capital commitments, maintain investor relationships, collaborate cross-functionally, and drive operational efficiencies for lending programs.

Develop fullstack web applications, enhance platform performance, collaborate on high-impact opportunities, and ensure stable, scalable solutions. Engage in rapid iterations and be a committed team player.

Lead technical direction and delivery of ML platform infrastructure (feature store, model serving, experimentation, training pipelines). Drive architecture, resolve system-level issues, write production code, mentor engineers, and partner with ML, data, and product teams to enable scalable, reliable ML model development and deployment.

Lead an Agile team to design, build, deploy, and maintain production-scale ML models and pipelines. Drive ML architecture, model training, CI/CD, monitoring, and cloud/Kubernetes-based deployments while ensuring responsible, explainable, and well-governed ML solutions.

Lead a cross-organizational program to transition engineering to an AI-driven, self-optimizing ecosystem with robust telemetry and evaluation. Orchestrate strategy and execution, mitigate technical risk, build and grow a TPM practice, align product/engineering/design/data science, and deliver measurable business impact.

Lead design, develop, test, deploy and support cloud-based data engineering solutions. Work across Agile teams on distributed, real-time and batch data platforms, mentor engineers, and optimize code and data pipelines using big data, streaming, and cloud data warehousing technologies.

Lead QA for an enterprise wealth-management platform: design and execute test plans, write and run API and integration tests, debug multi-layer issues, improve test coverage, mentor engineers, review release notes, and use tools/automation to ensure product quality.

Lead Product Designer for Arc Platform defining blockchain-native user experiences, economic clarity, and reusable design systems. Partner with Product and Engineering, set design direction, mentor designers, and ensure usability, trust, and scalability across platform surfaces.

Lead full outbound sales cycle for mid-market merchants, build and manage pipeline, craft multi-product Square solutions, run discovery/demos/negotiations, forecast in Salesforce, and consistently exceed revenue targets while collaborating cross-functionally.

Serve as first-line member support via chat and ticketing, resolving entry-level issues (payments, loyalty), triaging and escalating complex cases, documenting interactions, collaborating with internal teams and BPO partners, staying current on product changes, and delivering patient, organized digital customer service.

Lead full outbound sales cycle for mid-market merchants: prospect, build pipeline, run demos, negotiate multi-product deals, and close. Collaborate cross-functionally, act as trusted advisor, manage forecasting in Salesforce, and consistently exceed monthly and quarterly revenue targets.

Lead marketing analytics for US business: develop unified measurement (MMM, MTA), site analytics, forecasting, experimentation, and channel performance insights. Drive dashboards, collaborate with Data Science/Data Engineering to operationalize models, and present strategic recommendations to senior stakeholders to inform marketing spend and channel strategy.