Data Analytics Team Lead
Incode is an AI-driven identity verification and fraud-prevention company. It provides enterprise tools for identity and age verification, KYC/KYB/AML workflows, deepfake detection, workforce identity protection, and fraud analytics.
Projects
About Incode
Incode Technologies provides an enterprise identity orchestration platform that helps organizations verify customers, businesses, employees, and autonomous AI systems. Its products combine biometric and document verification, liveness and deepfake detection, fraud intelligence, analytics, case management, APIs, SDKs, and no-code workflow tools. It serves large organizations across financial services, healthcare, online gaming and gambling, e-commerce, public sector, and social media.
Skills
About the Role
You will lead and grow the analytics team while remaining hands-on with data pipelines, queries, and analysis. You will build product-quality metrics, dashboards, ML evaluation workflows, experiments, and data-quality controls. You will 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