Top Tech Jobs & Startup Jobs

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

Manage a portfolio of small and medium business customers to grow relationships and identify additional capital solutions. Analyze business and financial histories, own the sales process from approval to close, use data to prioritize opportunities, and meet monthly quota in a fast-paced environment.

Manage a portfolio of 800+ arbitration matters end-to-end: draft and review pleadings, briefs, discovery, evidentiary submissions, settlement agreements, and assist with courtroom litigation, subpoenas, AI/automation workflows, and general legal/account servicing. Communicate with customers and senior leadership and collaborate with cross-functional teams.

Design, build, and operate a low-latency online feature store and supporting batch/streaming pipelines. Optimize Postgres schemas and real-time serving for ML models, improve scalability, reliability, and observability, mentor junior engineers, and partner with data science, analytics, product, and application teams to deliver production-grade MLOps solutions.

This role is responsible for prospecting and converting financing applications, engaging with small business owners, and driving measurable sales results through lead conversion.

The Senior Analyst, Portfolio Strategy will analyze pricing and credit strategies, manage portfolio risk, and support decision-making with data insights.

Design, build, and operate HubSpot-based lifecycle and trigger-driven customer journeys using AI to scale personalization. Maintain CRM data integrity and Salesforce sync, ensure compliance and deliverability, and translate campaign performance into actionable insights and reports.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead technical design and architecture for analytics engineering: build and govern the semantic/metrics layer, optimize dbt and Snowflake for performance and AI use cases, mentor engineers, partner with Data Science and Engineering, drive data quality, CI/CD, observability, and deployment of third-party data and emerging tooling to support analytics, ML, and agent-based products.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.