Top Tech Jobs & Startup Jobs

Lead full life-cycle technical recruiting for engineering, QA, and design roles. Use AI and modern sourcing platforms to identify talent, build dashboards, manage pipelines, partner with hiring managers, and improve recruiting processes. Act as storyteller, closer, and data-driven advisor to scale the technology organization and enhance employer branding.

Drive Midwest SLED revenue by selling analytics-driven SaaS identity and fraud solutions. Build pipeline, manage full sales cycle, develop partnerships/channels, collaborate with product, forecast accurately, and travel up to 50% to close deals and ensure customer success.

Lead Socure's channel strategy and partner ecosystem to drive joint revenue, expand market reach, and deliver tailored partner solutions. Build and mentor a channel leadership team, align cross-functional stakeholders, establish program standards, track KPIs, and champion tools and processes to improve partner outcomes.

The Head of Data Science - Fraud Insights will lead research on fraud analytics, design predictive studies, manage a team, and communicate findings to influence strategy and policy.

Lead a new credit products line by defining vision, strategy, and roadmap for credit score and credit-adjacent offerings. Drive cross-functional execution with Data Science, Engineering, Legal, Compliance, GTM and Operations to build compliant, scalable products for lenders and financial services. Own product discovery, metrics, executive alignment, team hiring and development, and external thought leadership for CRA, BNPL, underwriting, and risk decisioning products.

Lead product marketing for Socure's document verification solutions: define positioning, go-to-market plans, and sales enablement. Conduct market and competitor research, support launches, create customer-facing content and collateral, track performance metrics, and gather stakeholder feedback to inform product and marketing strategies.

The Developer Marketing Lead will drive marketing strategies for APIs, engage with developers, and align messaging with Product and Engineering teams to enhance pipeline metrics and product adoption.

Develop and deploy production ML models for document verification and fraud detection. Perform model evaluation, experimentation, and analytics; build monitoring, tooling, and automation; partner cross-functionally to improve product performance and operational efficiency.

Develop ML features, models, and analytical methods from device, network, browser, mobile, session, and behavioral telemetry to detect fraud and improve identity confidence. Handle large-scale, noisy, high-cardinality data, design validations, assess drift and leakage, collaborate with engineering/product/risk for production rollout, document models and features, and mentor junior team members.

Lead development of production-grade fraud and identity risk signals from high-scale device, network, browser, mobile, API, and behavioral telemetry. Define evaluation methods, build scalable feature engineering, investigate adversarial signal patterns, influence telemetry and production readiness, mentor data scientists, and drive technical direction for robust, explainable, low-latency decisioning systems.