Socure

Recruitment

• Manage end-to-end interview scheduling for candidates, panels, and high-volume pipelines across multiple time zones
• Coordinate candidate and interviewer communications, provide timely updates, and ensure a positive and consistent candidate experience
• Maintain accurate candidate records, notes, interview feedback, and dispositioning in the applicant tracking system (ATS)
• Prepare interview materials, collect interviewer feedback, and coordinate candidate travel or virtual interview logistics as needed
• Support recruiting events, referral programs, and onboarding coordination in partnership with cross-functional teams
• Ensure compliance with recruiting processes, documentation standards, and applicable employment regulations
• Partner with recruiters and hiring managers to identify process improvements and implement best practices
• Source and identify candidates for open roles using LinkedIn Recruiter, job boards, internal talent pools, referrals, and other sourcing channels
• Conduct initial outreach to prospective candidates and support recruiter-led candidate engagement efforts
• Assist in building and maintaining diverse talent pipelines for current and future hiring needs
• Post and maintain job openings on Socure’s careers site and external job boards, ensuring consistent messaging and accurate job descriptions
• Track sourcing activity and pipeline health to support reporting and continuous improvement

Talent Sourcer – Coordinator

Product Marketing

• Administer and support Revenue Acceleration and AI initiatives, such as Momentum.io, Clari AI Agents, Clari Forecast AI, MEDDPICC scoring, Opportunity scoring, and Agentic AI capabilities.
• Act as a Salesforce power user: build and maintain reports and dashboards, troubleshoot data discrepancies, and collaborate with Salesforce Administrators to drive system automation and improvements.
• Manage integrations and reporting workflows across Salesforce, Google Sheets, and BI tools (e.g., Tableau).
• Own recurring operational workflows related to data quality, forecasting inputs, and system hygiene, with minimal supervision.
• Identify and implement opportunities to improve efficiency through advanced tooling, process automation, and technical optimization within the GTM funnel.
• Document processes, system logic, and operational runbooks to support scalability and knowledge transfer.
• Proactively identify and surface risks, gaps, and opportunities for improvement related to GTM systems and data.

GTM Operations Analyst

People Operations

• Own and execute pre-onboarding and onboarding for new hires, including welcome communications, first-day setup, benefits orientation, and coordination with local office partners.
• Serve as the primary HR point of contact for employees, supporting inquiries related to benefits, payroll, leave, policies, and People programs.
• Support local HR operations in India, ensuring alignment with regional labor laws, statutory requirements, and internal policies.
• Maintain accurate and timely employee data across HR systems, including Workday, 15Five, Ashby, covering new hires, job changes, organizational updates, and terminations.
• Partner with the Compliance and Finance teams to support audits, reporting, and documentation, including responding to internal and external audit requests.
• Generate and maintain reports for management, compliance, and operational insights.
• Support candidate background verification processes in partnership with First Advantage, ensuring timely completion and documentation.
• Maintain and continuously improve the People Ops Resource Center for India, ensuring content is accurate, accessible, and compliant.
• Design, document, and maintain Standard Operating Procedures (SOPs) and process documentation to ensure consistent execution and compliance with Indian labor laws and regulations.
• Provide operational oversight and coordination for leave management, absence tracking, and payroll processes, ensuring accuracy and compliance.
• Support managers, employees, HRBPs, and the Operations team by interpreting and applying leave policies, benefits programs, and People processes in a compliant manner.
• Maintain complete and accurate records related to leave, accommodations, and compliance documentation, following legal and best-practice requirements.
• Serve as a point of contact for Workday Learning (LMS) administration in India, supporting compliance training and reporting.
• Assist with the implementation, enhancement, and ongoing administration of payroll and benefits programs in India, including coordination with vendors and internal stakeholders.
• Identify opportunities to improve People Ops processes through better system usage, automation, and standardization.

Senior People Operations Specialist

Analyst

• Lead and define the end-to-end strategy for document labeling, manual verification, and transaction escalation across DocV.
• Examine identity documents such as passports, national ID cards, and driver’s licenses to assess authenticity, quality, and signs of manipulation or fraud, including complex and edge-case submissions.
• Serve as the primary escalation owner for high-risk or ambiguous transactions, supporting real-time customer decisioning and providing authoritative fraud assessments and rationale.
• Define, document, and maintain labeling standards, review criteria, escalation guidelines, and quality controls used for model training, validation, and customer-facing decisions.
• Own the creation and validation of labeled datasets for machine learning initiatives, ensuring consistency, accuracy, and alignment with evolving fraud patterns.
• Partner closely with data science, product, engineering, and fraud teams to inform model development, validate model outputs against real-world fraud cases, and refine tooling and workflows.
• Identify, analyze, and document emerging document fraud techniques and trends, translating findings into actionable guidance for models, processes, and customer use cases.
• Support the design and rollout of new DocV capabilities, including manual review workflows and video interview based verification, helping define operational processes and fraud evaluation frameworks.
• Act as a mentor and functional lead for forensic and review practices, setting the standard for analytical rigor, documentation, and decision quality.

Senior Forensic Document Analyst

Data Scientist

• Design, develop, and implement advanced deep learning models, including transformers, CNNs, and LSTMs, to address complex fraud and risk challenges.
• Build and optimize models using a variety of input data types, including tabular data, natural language, point clouds, and images.
• Lead the end-to-end machine learning lifecycle: data exploration, feature engineering, model training, evaluation, deployment, and monitoring in production environments.
• Take ownership of project outcomes, data quality, and delivery timelines; proactively escalate issues and work collaboratively to resolve challenges.
• Mentor and share knowledge with peers and junior data scientists, fostering a culture of experimentation, rapid iteration, and continuous learning.
• Collaborate cross-functionally with Product, Engineering, and Risk teams to define data requirements and drive insights that guide strategic decisions.
• Conduct in-depth research to explore new data sources and develop novel algorithms that advance the state of the art in fraud detection.
• Present findings and recommendations to technical and executive stakeholders with clarity and influence.
• Stay current with advancements in AI and machine learning, applying innovative approaches to real-world problems.
• Model Socure’s embedded leadership competencies: continuous learning, effective communication, accountability, team development, decision making, and managing change.

Staff Data Scientist – Fraud & Risk

• Design and deploy advanced machine learning systems for device identification, anomaly detection, and fraud prevention—balancing precision, recall, and real-world adversarial dynamics.
• Contribute to the development of scalable data pipelines and production ML workflows using structured and unstructured telemetry (e.g., browser, mobile, session data).
• Investigate high-complexity signals (e.g., emulator use, spoofing, low-entropy fingerprints), applying advanced statistical methods and domain knowledge to detect fraud and abuse.
• Translate ambiguous business problems into modeling approaches, using a combination of supervised, unsupervised, and heuristic techniques.
• Partner with engineering, product, and risk teams to contribute to data architecture decisions, signal collection, and planning.
• Drive experimental design, A/B testing frameworks, and robust validation techniques to ensure model generalizability and long-term trust.
• Contribute to team standards for ML explainability, risk evaluation, and feature logging.
• Document methodologies and communicate results effectively through dashboards, presentations, and reports for both technical and executive audiences.
• Mentor junior data scientists and participate in cross-functional working groups.

Senior Data Scientist – Digital, Device Intelligence

Backend Engineer

• Architect, develop, test, and debug scalable backend services within distributed systems.
• Own and deliver key non-functional requirements, including scalability, availability, performance, and security.
• Author and maintain comprehensive tests (unit, integration, functional) to ensure exceptional coverage and reliability.
• Produce and contribute to technical documentation for internal knowledge sharing and external collaboration.
• Decompose complex projects into clear, actionable tasks and drive them through to completion.
• Mentor and support engineers through code reviews, technical guidance, and sharing of best practices.
• Collaborate cross-functionally with product managers, designers, and engineers to deliver impactful features.
• Continuously enhance engineering processes, tools, and practices within an agile environment.

Senior Backend Engineer

Engineering Manager

• Architect and design scalable, resilient, high-performance backend systems and platforms in AWS
• Contribute hands-on to key initiatives
• Lead cross-team technical initiatives
• Partner closely with Product, Design, Data Science, and Platform teams
• Own design of APIs and microservices
• Advance operational excellence
• Solve complex distributed system challenges
• Document architectural decisions
• Foster team growth through clear expectations

Manager, Software Engineering

• Design, develop, test, and debug components for distributed systems that operate at large scale and high speed
• Own and drive nonfunctional requirements such as scalability, availability, and security
• Develop and maintain unit and integration tests, achieving robust code and functional coverage
• Produce enterprise-class documentation for internal and external collaboration
• Break down complex tasks into manageable components, plan, and execute effectively
• Collaborate with team members to elevate technology standards and consistently apply best practices
• Participate actively in an agile environment to deliver high-quality software solutions

Frontend Engineer

• Develop robust user interfaces from high-fidelity designs and functional specifications of varying complexity.
• Collaborate with product managers, designers, and engineers to deliver an exceptional, customer-centric product.
• Own features end-to-end, from design reviews to production rollout, ensuring high quality, usability, and performance.
• Create comprehensive unit, integration, and end-to-end tests for robust code and broad functional coverage.
• Break down complex technical and product challenges into actionable tasks and drive them to successful completion.
• Contribute to the evolution of our design systems and frontend architecture to enhance scalability, maintainability, and developer experience.
• Partner with backend and infrastructure engineers to define efficient APIs and data contracts.
• Mentor and coach fellow engineers by sharing expertise, conducting code reviews, and promoting engineering best practices.
• Champion accessibility, performance, and security throughout frontend development.
• Work in an agile, fast-paced environment focused on rapid delivery and continuous improvement.

Senior Frontend Engineer

• Design, develop, and implement advanced deep learning models, including transformers, CNNs, and LSTMs, to address complex fraud and risk challenges.
• Build and optimize models using a variety of input data types, including tabular data, natural language, point clouds, and images.
• Take ownership of assigned tasks, executing technical and functional activities to support project goals with minimal supervision.
• Participate in all stages of the machine learning lifecycle: data exploration, feature engineering, model training, evaluation, and deployment.
• Collaborate effectively across teams, sharing knowledge and learning from diverse perspectives to drive results.
• Make routine technical decisions and contribute to functional objectives through productive and proactive engagement.
• Stay current with advancements in AI and machine learning, applying innovative approaches to real-world problems.
• Communicate results and insights clearly to both technical and non-technical audiences.

Data Scientist II – Fraud & Risk

Pricing Analyst

• Develop, analyze, and maintain cost and pricing models for subscription, transactional pay-per-use (API), and enterprise licensing data products.
• Partner with Product Managers to analyze, recommend, and test tiered, volume-based, and bundled margin and pricing structures.
• Support monthly, quarterly, and annual cost and price reviews and recommend adjustments based on market data and company strategy.
• Evaluate data acquisition and licensing costs across vendors and data sources.
• Model and monitor gross margins for data products to ensure profitability targets are met.
• Provide Product, Finance and Revenue Leadership with visibility into cost drivers and margin sensitivity under different pricing scenarios.
• Analyze vendor and internal data usage patterns against spend and revenue to develop return-on-investment recommendations and decisions.
• Collaborate with Finance to support forecasting, scenario modeling, and revenue planning.
• Maintain data cost information with global data vendors to ensure all cost inputs are accurate and current.

Global Data Cost and Pricing Analyst

Product Manager

• Own the vision, strategy, and roadmap for RiskOS Case Management - evolving and scaling existing capabilities into a best-in-class reviewer experience.
• Convert customer and internal pain points into crisp problem statements, requirements, and measurable outcomes (e.g., time-to-decision, throughput, quality).
• Lead consolidation across product lines into a unified, consistent case management dashboard (queues, case views, actions, reporting).
• Run continuous discovery with fraud/risk/compliance teams and GTM/sales (interviews, shadowing, usability testing) and turn insights into roadmap priorities.
• Drive alignment across Product, Design, Engineering, Data Science/ML, Analytics, and GTM on priorities, sequencing, and tradeoffs.
• Communicate clearly with executives and stakeholders; sustain velocity while protecting UX quality and platform scalability.
• Ensure execution and launch readiness for major releases: enablement, release planning, adoption tracking, and post-launch iteration.

Staff Product Manager – Risk & Compliance Case Management

• Lead the evaluation and continuous improvement of entity resolution and entity linking pipelines.
• Debug new builds, identify anomalies, and recommend modeling or system-level improvements.
• Define, implement, and maintain scalable performance and quality metrics, leveraging automation and LLM-based approaches where appropriate.
• Partner with Engineering to optimize entity linking and ranking systems using Learning-to-Rank and related techniques.
• Design methods to assess and classify entity confidence and quality across the graph.
• Design and implement a comprehensive data quality framework for graph-based identity data.
• Translate abstract quality concepts (e.g., reliability, stability, consistency) into measurable signals.
• Identify and operationalize generalized, high-impact predictive signals derived from graph structure, temporal dynamics, and relational patterns.
• Collaborate closely with Engineering, Product Management, Compliance, and downstream product teams.
• Act as a technical leader within the Identity organization, influencing modeling standards, experimentation rigor, and best practices.

Staff Data Scientist – Identity Graph

• Own the strategic vision and execution for Socure’s identity graph
• Lead innovation in identity graph technologies
• Cross-functional leadership and influence at scale
• Mentorship and graph-focused thought leadership
• Shape company-wide outcomes through graph innovations
• Represent Socure externally as a graph expert
• Develop and execute go-to-market strategy

Talent Sourcer – Coordinator

GTM Operations Analyst

Senior People Operations Specialist

Senior Forensic Document Analyst

Staff Data Scientist – Fraud & Risk

Senior Data Scientist – Digital, Device Intelligence

Senior Backend Engineer

Manager, Software Engineering

Senior Backend Engineer

Senior Frontend Engineer

Data Scientist II – Fraud & Risk

Global Data Cost and Pricing Analyst

Staff Product Manager – Risk & Compliance Case Management

Staff Data Scientist – Identity Graph

Staff Product Manager – IDGraph