Data Analytics Team Lead
Incode Technologies is an AI-powered identity verification and fraud prevention company. It provides identity, biometric, liveness, KYC/KYB, authentication, age assurance, and deepfake-defense solutions for global enterprises, including financial institutions, fintechs, marketplaces, governments, telcos, healthcare organizations, and gaming companies.
Maintainer signals as of 8/23/2026
Funding history
About Incode Technologies, Inc.
Incode develops and operates an identity platform that verifies users, businesses, and AI agents through document verification, biometrics, facial recognition, liveness detection, deepfake detection, government-record matching, sanctions and PEP screening, and risk decisioning. Its platform includes configurable verification workflows, case management, analytics, integrations, and developer SDKs. The company serves enterprise customers across financial services, fintech, crypto, commerce, marketplaces, public sector, healthcare, travel, telecommunications, gaming, and other industries.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Lead and grow the analytics team while remaining hands-on with data pipelines, queries, analysis, product-quality metrics, dashboards, ML evaluation workflows, experiments, and data-quality controls. Translate data gaps into prioritized requirements for engineering and turn ad hoc analysis into repeatable reporting.
Requirements
- Team leadership experience while remaining hands-on
- Strong Python skills and clean, maintainable code practices
- Strong SQL skills and experience with columnar or analytical databases
- Strong statistics and experimental-design skills, including significance and power analysis
- Experience with workflow orchestration, data transformation, cloud storage, and experiment tracking
- Excellent communication skills for translating data gaps into business-justified requirements
- Ownership, autonomy, and pragmatic prioritization
Responsibilities
- Lead, manage, mentor, and hire for the analytics team
- Write SQL and Python pipelines for data collection, processing, and labeling
- Build an end-to-end metric tree for document-processing product quality
- Create reporting and dashboards for ML, product, and leadership
- Prepare data for ML evaluation, assess model quality, and benchmark models
- Design, run, and interpret A/B tests across mobile and server-side systems
- Monitor and improve data and labeling accuracy and consistency
- Define missing data requirements and write prioritized tasks for backend and data teams
- Turn one-off analyses into repeatable pipelines and reporting cadences
Benefits
- Flexible working hours and workplace
- Open vacation policy