Data Analytics Team Lead

incode; United States; Remote; USD 120,000 - 190,000; Full time

Job summary

incode Lead Analytics Engineer role leading a small analytics team while staying hands-on in data work that measures and improves document-processing quality. The role spans analytics strategy, team development, pipeline building, experimentation, and machine-learning evaluation, expanding measurement coverage and making product quality and performance visible to technical and business partners.

You will own the analytics roadmap, mentor analysts, conduct regular reviews, and contribute to

Qualifications

• Experience leading analytics teams while staying hands-on.
• Strong Python skills and maintainable code.
• Strong SQL skills and experience with columnar databases.
• Solid statistical knowledge and experimental design skills.
• Ability to turn unclear data needs into specific tasks and explain business value.
• High ownership, sound judgment, and clear communication in evolving environments.

Responsibilities

• Own the analytics roadmap, manage and develop analysts, conduct regular one-to-ones and performance reviews, and contribute to hiring.
• Build and maintain data collection, processing, and labeling pipelines using SQL and Python, and personally conduct analyses.
• Develop an end-to-end metric framework for quality across the document-processing pipeline.
• Create reporting and dashboards that reveal weak points and give ML, product, and leadership teams actionable insights.
• Partner with machine-learning colleagues on data preparation, model-quality evaluation, and benchmarking.
• Design and interpret rigorous A/B tests across mobile and server systems; improve data and labeling quality controls.

Skills

Python

SQL

Statistics

Data analysis

Team leadership

Communication

Tools

Pandas

SQL databases

A/B testing frameworks

Job description

Role overview

Lead a small analytics team while remaining directly involved in the data work that measures and improves document-processing quality. The role spans analytics strategy, team development, pipeline building, experimentation, and machine-learning evaluation. Its central goal is to expand measurement coverage and make product quality and performance visible to technical and business partners.

Responsibilities

• Own the analytics roadmap, manage and develop analysts, conduct regular one-to-ones and performance reviews, and contribute to hiring.
• Build and maintain data collection, processing, and labeling pipelines using SQL and Python, and personally conduct analyses.
• Develop an end-to-end metric framework for quality across the document-processing pipeline.
• Create reporting and dashboards that reveal weak points and give ML, product, and leadership teams actionable insights.
• Partner with machine-learning colleagues on data preparation, model-quality evaluation, and benchmarking.
• Design and interpret rigorous A/B tests across mobile and server systems; improve data and labeling quality controls.

Requirements

• Experience leading or managing an analytics team, with a willingness to stay hands-on in analysis and implementation.
• Strong Python skills and ability to write maintainable, reusable code.
• Strong SQL skills and experience with columnar or analytical databases.
• Solid statistical knowledge and experimental design skills, including evaluating significance and test power.
• Ability to turn unclear data needs into specific engineering tasks and explain their business value.
• High ownership, sound judgment, and clear communication in an evolving environment.

Nice to have

• Experience evaluating machine-learning products and working with ML teams.
• Familiarity with data labeling workflows and methods for measuring and maintaining label quality.
• Exposure to identity documents, OCR, or computer-vision pipelines.

Benefits and work setup

The source describes flexible working hours and workplace arrangements, an open vacation policy, and a culture emphasizing autonomy, responsibility, feedback, and professional development.