Socure

Digital Marketing

• Drive Socure's digital marketing vision, strategy, and execution with AI and marketing agents at the core
• Lead the digital marketing team and partner with cross-functional stakeholders
• Build AEO and SEO programs to increase Socure's AI-assistant visibility and traditional rankings
• Run full-funnel paid media across Google, LinkedIn, Meta, LLM Ads, programmatic, and emerging AI ad surfaces
• Use AI for targeting, creative variation, bid strategy, and budget reallocation
• Build agent-driven lifecycle programs that respond to buying signals and coordinate handoffs with Sales Development and ABM
• Turn socure.com into an adaptive, personalized website with conversational paths to demos
• Design and operate an agentic marketing engine converting market signals into content and campaign assets
• Establish human-in-the-loop review for accuracy, brand, and compliance
• Build attribution and reporting connecting AI visibility, paid, lifecycle, and web engagement to pipeline and bookings
• Lead and grow teams across paid, organic/AEO, lifecycle, and digital operations
• Mentor team members to work effectively alongside AI agents
• Deliver first-year outcomes including AI-assistant citations, increased qualified pipeline contribution, live agentic workflows, improved demo conversion, and faster higher-quality team output

Head of Digital Marketing, AI-Driven Growth

Product Operations

• Build and lead a small Launch Operations team
• Maintain clear visibility across upcoming product launches
• Keep cross-functional teams aligned using the Product Manager-owned launch checklist
• Prioritize essential launch elements to track and report on
• Run a weekly launch accountability forum and launch check-in
• Spot risks early, test resolution plans, and keep work moving without taking on task execution
• Maintain accountability across major PR and investor launches, feature updates, and strategic initiatives
• Shift checklist ownership to functional leads
• Refine the launch checklist with Product Operations teammates
• Share updates and digests with Product Marketing, Legal, Engineering, Support, and RevOps
• Pull target launch dates from roadmap tools such as Aha! or Jira
• Establish criteria for entering the launch checklist process, typically 6–12 weeks before launch
• Adapt Product Operations systems and tools as tracking views are automated and operational systems mature
• Ensure executive leadership has accurate launch status visibility
• Ensure checklist items are assigned, dated, visible, and progressing
• Drive recovery plans and escalation for at-risk items and blockers
• Scale the launch cadence across major releases and new capabilities
• Provide commercial and field teams with timely visibility into launch timelines and feature availability
• Prove the value of the senior IC role and eventually build and lead a team tracking launch health across strategic initiatives

Principal Product Operations Manager – Launches

Account Executive

• Own a greenfield territory and lead high-impact sales efforts for AI-powered identity and fraud solutions
• Lead growth across greenfield opportunities and existing accounts
• Develop expansion strategies to deepen product adoption and maximize account value
• Manage full-cycle enterprise SaaS sales from prospecting to close
• Target high-value SaaS deals with innovative, fast-growing companies
• Build and maintain a robust pipeline through outbound prospecting and executive-level engagement
• Align complex technical solutions with customer needs in fraud, analytics, and digital identity
• Collaborate with product, engineering, and marketing teams to align on customer needs and influence the product roadmap
• Deliver accurate pipeline forecasts and support strategic planning
• Represent Socure at industry events and deepen client relationships through in-person meetings as needed

Account Executive Director – Crypto, Stablecoin

Product Designer

• Understand builder goals, technical constraints, operational needs, and adoption barriers with researchers, product managers, engineers, solution consultants, and customers
• Conduct customer interviews, usability studies, workflow reviews, competitive research, and product-data analysis
• Synthesize research and product signals into themes, opportunities, user needs, and design implications
• Build domain fluency in identity verification, fraud prevention, KYC, watchlist screening, compliance, and risk decisioning
• Frame ambiguous business and customer needs as problems, measurable outcomes, and design hypotheses
• Map end-to-end customer and user journeys across discovery, onboarding, configuration, integration, decisioning, case management, operations, and ongoing use
• Generate, compare, prototype, test, and iterate on multiple solution approaches
• Design workflows for onboarding, configuration, agent interaction, API keys, test identities, sandbox testing, usage visibility, case management, production readiness, and operations
• Design all relevant product states, including loading, empty, success, validation, permissions, errors, unavailable services, uncertain results, and recovery
• Produce detailed designs and specifications for accurate and efficient engineering implementation
• Connect interfaces, APIs, documentation, dashboards, hosted UI, agentic interactions, developer tools, and operational workflows
• Partner through implementation, review working software, perform design QA, and refine experiences using behavior and feedback
• Present work, explain tradeoffs, respond to critique, and make decisions visible to cross-functional partners
• Use AI tools to accelerate research synthesis, content exploration, flow generation, prototyping, critique, documentation, and design QA
• Develop responsible AI-assisted design patterns covering privacy, security, transparency, human oversight, and customer information
• Contribute reusable patterns to Socure’s design system
• Improve consistency between Figma, coded components, documentation, and shipped product behavior
• Share methods, findings, and feedback through critiques, working sessions, and cross-functional reviews
• Help reduce customer time-to-value, implementation and support effort, and increase product clarity, confidence, design throughput, accessibility, consistency, and trustworthiness

Senior Product UX/UI Designer

Systems Engineer

• Own and evolve systems supporting product planning, engineering execution, portfolio management, and cross-functional delivery
• Serve as technical owner for Jira, Aha!, and related product and project management platforms
• Manage configuration, administration, upgrades, permissions, security, integrations, data quality, and maintenance
• Design and maintain workflows, schemas, fields, templates, automations, dashboards, and reporting structures
• Ensure platforms are reliable, performant, secure, and aligned with company policies
• Establish platform configuration standards and reduce unnecessary customization, duplication, and fragmentation
• Maintain documentation for platform architecture, integrations, workflows, ownership, and support procedures
• Partner with Product, Engineering, Technical Program Management, Finance, and IT teams to translate requirements into system designs
• Improve representation of initiatives, roadmaps, epics, dependencies, capacity, milestones, intake requests, and delivery risks
• Lead implementation of product, engineering, portfolio, and work-management capabilities
• Build and maintain integrations among Jira, Aha!, Confluence, GitHub or GitLab, Slack, Workday, financial systems, BI tools, and other enterprise applications
• Use APIs, webhooks, automation frameworks, and integration platforms to reduce manual work and improve data consistency
• Support data migrations, platform consolidations, tool replacements, and major configuration changes
• Develop testing, validation, rollback, and change-management plans for releases
• Define and enforce standards for fields, hierarchies, workflows, permissions, naming conventions, and ownership
• Monitor system usage and identify inconsistent practices, stale data, redundant fields, and reporting gaps
• Build controls improving roadmap, delivery, capacity, dependency, and financial reporting accuracy
• Establish intake and prioritization for platform enhancement requests
• Assess platform fit and contribute to future-state tooling recommendations
• Build dashboards and reporting for roadmap progress, delivery status, dependencies, risks, capacity, and carryover
• Support analytics and business intelligence integrations and define platform effectiveness metrics
• Provide advanced support and troubleshooting for complex platform issues
• Create documentation, training materials, office hours, and platform guidance
• Coach system administrators and power users
• Communicate platform changes and help teams transition to new workflows and capabilities
• Build a network of business owners and power users to reinforce consistent practices

Senior Business Systems Engineer – Product & Engineering Platforms

Program Manager

• Own end-to-end execution of Socure’s performance operating system, including goal-setting, check-ins, feedback, recognition, and performance reviews
• Design performance cycles, calendars, configurations, communications, training, and post-cycle retrospectives
• Administer and optimize performance platforms such as 15Five and Workday
• Track platform adoption and enable managers and employees
• Design and run recognition programs and measure their impact on engagement and retention
• Build and facilitate calibration processes for performance ratings
• Partner with People Partners on manager enablement and bias mitigation
• Partner with Total Rewards to connect performance outcomes to compensation decisions
• Use People Analytics, dashboards, platform insights, and generative AI to synthesize data, generate reports, and identify trends
• Build and maintain playbooks, templates, manager guides, and communications
• Identify opportunities to automate recurring workflows
• Partner with HRBPs, HR Tech, Total Rewards, and business leaders to drive adoption and localization
• Serve as the day-to-day contact for performance program questions and escalations
• Monitor market practices and incorporate benchmarks and emerging approaches into program design

Senior Program Manager, Performance

Data Scientist

• Improve the quality, coverage, and freshness of Watchlist data through next-generation ingestion pipelines
• Design and execute data quality analysis pipelines to identify anomalies, evaluate dataset health, and ensure high-fidelity model-training inputs
• Apply NLP and AI to classify and enrich raw source data into normalized schemas
• Extract structured entity attributes from unstructured sanctions, PEP, adverse media, and enforcement sources
• Expand multilingual capabilities across Latin and non-Latin scripts
• Build NLP systems for entity resolution, deduplication, alias resolution, and canonical profiles
• Develop approaches for evolving entity profiles, names, aliases, and sanctions status
• Measure and benchmark entity resolution quality and improve coverage and accuracy
• Design and scale real-time name-matching and identity-classification models
• Build multi-signal risk scoring using name similarity, entity type, geography, list type, and other attributes
• Maintain benchmarking frameworks, golden datasets, and regression tests
• Build analytics for customer screening-threshold tuning
• Develop backtesting and counterfactual analysis capabilities
• Design evaluation frameworks for AI-powered autonomous decision systems and monitor production drift
• Develop mathematical analysis and feature engineering for AML risk patterns in transaction data and payment message fields
• Maintain AML taxonomy and risk signal library
• Apply graph-based methods to identify indirect sanctions-risk exposure
• Lead technical initiatives across Watchlist Data Science
• Collaborate with Product and Engineering to bring research into production systems
• Prototype and deploy advances in NLP, large language models, and entity resolution
• Mentor peers and contribute to technical rigor and continuous improvement

Staff Data Scientist, Watchlist

• Own end-to-end execution of Socure’s engagement survey program, including lifecycle surveys, survey design, vendor/tool management, communications, reporting, analysis, and action planning
• Consolidate engagement, pulse, exit, and listening data into reporting views and dashboards
• Identify trends and drivers and track action-plan progress
• Support operating model design and rollout, including role definitions, decision rights, team structures, facilitation, documentation, and change management
• Build and maintain organizational health diagnostics and dashboards covering turnover, span of control, engagement, performance distribution, and headcount health
• Translate diagnostic findings into recommendations through root-cause analysis
• Develop and own Socure’s change management practice, playbook, toolkit, and frameworks
• Partner with the AI Ops Committee, HRBPs, and business leaders on AI-driven changes to workflows and operating models
• Plan and execute strategic talent and culture projects and organizational assessments
• Build repeatable playbooks, templates, and documentation; automate and streamline workflows using AI-enabled tools
• Partner with HRBPs, HR Leadership, and business leaders to ensure adoption, inclusion, and data-grounded decisions
• Serve as day-to-day contact for program questions and escalations
• Monitor market practices, benchmarks, and frameworks in organizational effectiveness, engagement measurement, and change management

Program Manager, Org Effectiveness – Insights

Consultant

• Serve as a primary technical point of contact throughout the sales cycle and product implementation process for Socure's core identity verification products
• Understand client needs and match them to solutions using Socure's products
• Collaborate with Sales on business development, product and solution presentations, statements of work, and pricing
• Collaborate with Data Science on Proof-of-Concept design and execution
• Tailor strategies and recommendations for prospective clients using industry and domain expertise
• Partner with Product Development to surface client feedback and funnel product innovation concepts to product managers
• Contribute thought leadership with Product Marketing through blogs, whitepapers, research briefs, webinars, and more
• Translate between technical and non-technical audiences internally and externally
• Support stakeholder meetings to align resources and prioritize projects for business results
• Serve as a day-to-day technical resource for sales-related external and internal projects and engagements, supporting direct field sales and channel sales teams
• Mentor junior members of the Solution Consulting team as needed

Senior Solution Consultant, Core

Software Engineer

• Define and execute developer marketing strategy across awareness, activation, and retention for Socure's API and platform products
• Develop developer ICPs, technical value propositions, use cases, and competitive positioning
• Partner with Product and Engineering to incorporate differentiated data, capabilities, and insights into developer-facing narratives
• Translate AI-driven identity and fraud capabilities into technically credible content
• Deliver integration guides, technical decks, API playbooks, sandbox environments, and developer ROI tools
• Build and execute campaigns generating qualified pipeline from technical audiences, including product-led growth motions
• Drive awareness in developer communities, forums, and ecosystems
• Own technical blogs, documentation improvements, video walkthroughs, webinars, and conference presence
• Partner with RevOps to define success metrics, analyze funnel performance, and iterate from first touch to activation
• Act as developer marketing owner during planning cycles, QBRs, and product launches
• Influence Product, Engineering, Sales, DevRel, and Marketing to align product development and positioning
• Establish and track KPIs for developer signups, API activations, sandbox-to-production conversion, and technical pipeline contribution
• Bring market insights, developer community signals, competitive intelligence, and industry trends into GTM strategy discussions

Developer Marketing Lead

WHY SOCURE?

Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.

We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.



Job Summary:

Socure is the leading provider of digital identity verification and fraud prevention solutions, leveraging AI and machine learning to power the most accurate decisions. Our mission is to eliminate identity fraud and ensure online trust across industries.



RiskOS is Socure’s AI-powered orchestration and decisioning platform, providing a centralized control plane for identity, fraud, and risk workflows across the customer lifecycle.

Workforce Verification is a key RiskOS vertical focused on stopping workforce identity fraud—fake applicants, deepfake interviews, identity rental, and ghost employees—before they reach recruiters, systems, or sensitive data.



As a Data Scientist for Workforce Verification on the RiskOS team, you will own the end-to-end data science lifecycle for a critical new product area focused on workforce identity and hiring fraud. You will explore and analyze rich, multi-source data (identity, device, behavioral, resume and application signals) to uncover fraud patterns in the hiring funnel, then translate those insights into rules, conditions, and machine learning models deployed within RiskOS workflows.



This role sits at the intersection of fraud analytics, natural language processing, and Generative AI. You will help design and evaluate GenAI-powered components such as resume verification agents and explanation tools that operate on unstructured, text-heavy data like resumes, job descriptions, and interview artifacts.



The role is hands-on but not a “solo act”: you will be embedded in the RiskOS Data Science team, with guidance from senior data scientists and close partnership with product, engineering, and Workforce GTM. It is ideal for a data scientist with strong fraud or risk experience who wants broader end-to-end ownership, enjoys working with unstructured text, and is comfortable rolling up their sleeves on data engineering and productionization when needed.



Job Responsibilities:



 - Own the full data science lifecycle for Workforce Verification use cases on RiskOS—from data exploration and hypothesis generation through model development, evaluation, deployment, and monitoring.

 - Explore and analyze workforce-related data sources (applications, resumes, device and behavioral telemetry, background checks, ATS/HRIS integrations) to identify patterns of workforce fraud such as fake resumes, identity rental, deepfake interviews, and injection attacks.

 - Design, implement, and iterate on rules, conditions, and heuristic logic in RiskOS workflows to detect high-risk workforce events (e.g., repeated identities across multiple resumes, suspicious device patterns, anomalous hiring flows).

 - Develop and evaluate machine learning models for workforce risk and identity assessment (e.g., scoring applicants for fraud risk, clustering related identities, anomaly detection over hiring funnels), leveraging Socure’s broader identity and device signals where appropriate.

 - Collaborate with the RiskOS and Workforce product teams on GenAI-powered features such as the Resume Verification Agent and explanation agents—help define inputs/outputs, build evaluation datasets, and design quantitative and qualitative evaluation frameworks for LLM-based components.

 - Partner closely with engineering to productionize models, rulesets, and GenAI components within RiskOS: define interfaces, support integration and testing, and contribute to monitoring, alerting, and feedback loops.

 - Work with product, Workforce GTM, and solution consulting to translate model and rule performance into clear, customer-facing narratives (e.g., impact on blocking fake applicants, reducing deepfake interviews, or preventing identity rental in hiring).

 - Incorporate feedback and outcome data from customers to continuously improve Workforce Verification logic and models; support experimentation and offline “test harness” design to safely evaluate new workflows and templates.

 - Operate with a product mindset and strong ownership: document assumptions, decisions, and evaluation results; communicate trade-offs clearly; and proactively surface risks, limitations, and opportunities.
























Job Requirements:



 - Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field, or equivalent practical experience.

 - 3–6 years of hands-on experience in data science, machine learning, or applied analytics, with meaningful work on fraud, risk, trust & safety, or workforce/hiring analytics preferred.

 - Experience owning end-to-end analytics and/or model development projects: problem framing, data wrangling, feature engineering, model training, evaluation, and deployment support.

 - Strong proficiency in Python and SQL, including experience with common data science and ML libraries (e.g., pandas, scikit-learn, XGBoost, PySpark, or similar).

 - Comfort working with large, messy, and heterogeneous datasets (JSON workflows, logs, event streams, third-party enrichments) and building reusable abstractions or utilities to make them usable for yourself and others.

 - Exposure to Natural Language Processing and/or unstructured text analytics—such as resume or document parsing, entity extraction, similarity search, or basic embedding-based methods—ideally applied in real-world products.

 - Some hands-on experience working with Generative AI or LLM-based products (e.g., using commercial LLM APIs, prompt design, RAG-style retrieval, or evaluation of LLM outputs), with an interest in deepening this skill set.

 - Strong analytical and problem-solving skills, including comfort reasoning about ambiguous signals and adversarial behavior in fraud or workforce contexts.

 - Ability and willingness to take on light data engineering and production-oriented tasks when needed (e.g., building ETL transforms, contributing to Airflow/Spark jobs, or instrumenting basic monitoring) in partnership with engineering.

 - Clear, concise communication skills and the ability to explain complex analyses, models, and GenAI behavior to non-technical stakeholders (product, GTM, customers).

 - A bias toward ownership, learning, and collaboration—comfortable working in a fast-paced, evolving environment, receiving guidance from senior data scientists while steadily increasing your own scope and autonomy.



 - Nice to have:
   
   - Direct experience with workforce, HR tech, ATS/HRIS data, or hiring funnel analytics.
   
   - Prior work on identity verification, device intelligence, or orchestration/rules engines (e.g., RiskOS or similar systems).
   
   - Familiarity with evaluation and monitoring of GenAI systems (e.g., offline benchmarks, human-in-the-loop review, safety/hallucination checks).






Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.




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Data Scientist ll - RiskOS

• Drive strategic growth across Socure's Payments & Lending vertical
• Own a greenfield territory and lead high-impact sales efforts for AI-powered identity and fraud solutions
• Lead growth across greenfield opportunities and existing accounts
• Develop expansion strategies to deepen product adoption and maximize account value
• Manage full-cycle enterprise sales from prospecting to close
• Target high-value SaaS deals with innovative, fast-growing companies
• Build and maintain a robust pipeline through outbound prospecting and executive-level engagement
• Align complex technical solutions with customer needs in fraud, analytics, and digital identity
• Collaborate with product, engineering, and marketing teams
• Influence the product roadmap based on customer needs
• Deliver accurate pipeline forecasts and support strategic planning
• Represent Socure at industry events and deepen client relationships through in-person meetings as needed

Account Executive Director, Payments & Lending

• Own and administer the core product management and roadmapping platform, including workspaces, fields, workflows, scorecards, and permissions
• Maintain the connection between the product management platform and engineering work-tracking systems through field mapping and status synchronization
• Manage the broader product technology stack, evaluate tools, prevent tool sprawl, and maintain integrations across roadmap, delivery, feedback, and CRM systems
• Build and maintain intake and prioritization workflows
• Document system configuration and standard operating procedures
• Build dashboards and reports covering roadmap status, delivery progress, and portfolio health
• Define and track product operations metrics such as cycle time, roadmap adherence, planning hygiene, and tool adoption
• Centralize Product Performance metrics definition, telemetry builds, and availability to data and BI teams
• Coordinate dashboard and reporting builds with the central Business Intelligence team
• Partner with Finance, Sales/RevOps, and Engineering to incorporate commercial and delivery data into product prioritization and reporting
• Support business reviews, quarterly and annual planning, and board updates with trusted data
• Monitor data quality and drive hygiene standards
• Design and document repeatable planning, prioritization, intake, and roadmap-review processes
• Identify and resolve friction, manual work, and duplication through process, automation, or tooling
• Build templates, playbooks, and checklists for feature intake, roadmap reviews, and launch readiness
• Train product managers and embedded product operations partners through documentation and office hours
• Facilitate handoffs between Product, Engineering, Design, and GTM
• Standardize processes across product pods while preserving necessary flexibility
• Translate company priorities and strategy into trackable roadmaps and planning cadences
• Run quarterly and annual planning cycles, roadmap reviews, and business reviews
• Monitor strategic progress and flag misalignment between execution and leadership priorities
• Support trade-off and prioritization decisions
• Ensure pod-level work aligns with company strategic themes
• Ensure planning decisions are reflected in operational systems

Principal Product Operations Manager

• Analyze massive customer datasets and produce actionable insights
• Explain model performance and help customers build optimal risk-management policies
• Advocate for Socure’s solutions, products, models, and algorithms from a scientific perspective
• Create data stories demonstrating how Socure products eliminate identity fraud, streamline end-user experience, and support risk management
• Provide thought leadership and represent the customer voice in development of core models and products
• Create tools and automated workflows to improve analysis speed, accuracy, and reproducibility
• Partner with Sales, Solution Consultants, Account Managers, and Technical Account Managers to identify upsell and product-optimization opportunities
• Build machine-learning models when advantageous compared with established production models
• Support customer data, fraud and identity analytics, model evaluation, workflow optimization, monitoring/alerts, and reporting