Product Analyst, DocV

Posted 97ds ago

Employment Information

Industry

Education

Salary

Experience

Job Type

Location

Job expired or something wrong with this job?

Product Analyst owning data analysis for DocV at Socure. Focus on preventing fraud with analytical insights and collaborative efforts.

Own all data analysis related to Document Verification (DocV), and be the subject matter expert for this domain.
Perform ad-hoc and recurring analyses to support product decisions, answer key questions, and uncover emerging fraud patterns.
Build dashboards, alerting systems, and trackers to monitor product health, detect anomalies, and surface emerging issues (e.g., spikes in failure codes or fraud signals).
Maintain and expand a centralized fraud and transaction database, generating long-term insights into fraud trends, false positives, and model efficacy.
Collaborate with the Fraud Investigations (FI) team and manage labeling pipelines, monitor fraud trends, and incorporate findings into product development.
Support customer success and product scoping efforts with data-driven insights.
Conduct post-deployment performance analysis of fraud features, models, and new product capabilities.
Operationalize proactive monitoring of new ID types, data exceptions, and unusual classification behavior.
Manage our model governance process to regularly evaluate model performance and bias testing.

2+ years of experience in product analytics, data analysis, or a similar role in a data-focused environment.
Excellent communication skills with the ability to present complex findings to technical and non-technical audiences, and experience communicating insights to external customers or client-facing teams is a very strong plus.
Proficient in SQL and comfortable working with large datasets in cloud environments like Databricks, Snowflake, Mixpanel, or similar.
Experience with data visualization and dashboarding tools (e.g., Looker, Tableau) and a track record of building executive-ready dashboards.
Familiarity with Python for data analysis (e.g., Pandas, Jupyter Notebooks) is a plus.
Strong problem-solving skills and attention to detail; ability to dig deep into transactional data to uncover insights, with a solid statistical foundation to support rigorous analysis.
Prior experience in identity verification, fraud detection, or risk analytics is a strong plus.