Remote
$68k–$112k
middle
1 month ago
full-time
quality 8.6/10
What You'll Own & Drive
- Root Cause Investigation — Independently investigate data quality issues end-to-end. When a model metric drops or data looks wrong, you own the investigation: forming hypotheses, querying across data sources, and delivering a clear, evidence-backed answer.
- Automated Data Pipelines — Design, build, and maintain pipelines for collection, labeling, validation, and metric computation that support ML training and evaluation.
- Data & Labeling Quality Standards — Establish and monitor consistency checks, accuracy audits, and root-cause analysis when issues impact model outcomes.
- Model Evaluation Metrics — Define, implement, and automate evaluation metrics and reporting that reflect real-world product use cases and business goals.
- Performance Tracking Systems — Build scalable dashboards and monitoring to enable fast, data-driven decisions across teams.
- Workflow Orchestration — Develop and operate reliable orchestration (Airflow, Prefect, or similar) to schedule, observe, and troubleshoot end-to-end pipelines.
- Clean, Maintainable Code — Write SQL and Python to efficiently investigate problems — querying databases, calling internal APIs, and processing data across multiple sources.
- Cross-Functional Partnership — Partner closely with ML engineers, analysts, and product stakeholders to prioritize work by impact, unblock execution, and continuously improve internal tooling for analysis and evaluation.
Your Background
- 3+ years of experience as a Data Analyst or in a similar data infrastructure role.
- Strong SQL and Python skills for data investigation and root cause analysis.
- Hands-on experience with AWS Redshift or a similar columnar/cloud database (BigQuery, Snowflake, etc.).
- Solid statistical foundation — you can reason about rates, distributions, significance, and sampling bias.
- Hands-on experience with workflow orchestration tools (Airflow, Prefect, Dagster, etc.).
- Proven experience in data quality management, data preparation, or ML data pipelines.
- A proactive mindset toward identifying problems.
- Strong collaboration and problem-solving skills.
- Background in mathematics, physics, or engineering.
Why Incode?
- Mission with Meaning — Build systems that enable ethical, seamless identity verification for millions.
- Rocket-Ship Growth — Join a company scaling globally with AI at its core.
- Elite Team & Technology — Collaborate with top engineers and data scientists redefining document intelligence.
- Ownership & Autonomy — Operate with end-to-end responsibility for impactful data pipelines.
- Global Impact — Your work will power real-world AI experiences trusted by major enterprises.
Benefits & Perks:
- Flexible Working Hours & Workplace
- Open Vacation Policy
- Equal Opportunities: Incode is an equal opportunity employer, committed to creating a diverse and inclusive work environment.
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