Data Analyst

About iVerify

We are Experts in Mobile Threat Hunting. The first mobile threat hunting company to protect mobile devices like any other vulnerable corporate endpoint.

The mobile security market has a problem. Simply put, current solutions fail to meet the sophistication of modern threats or the growing privacy desires of mobile device users. We believe that it is time for something new. Not only because we care deeply about the safety of frontline users like journalists and activists - many of whom are doing important and often dangerous work - but because enterprises and consumers deserve real protection from advanced mobile threats without sacrificing privacy.

We are building the first mobile threat hunting company to harmonize security and privacy in the face of a new class of mobile threats. Supported by some of the most well-respected VC firms, we aim to become the go-to mobile security solution for individuals who want to know they can trust their devices with their most sensitive information – without sacrificing privacy.

We are seeking a Data Analyst to help transform iVerify’s growing dataset into actionable insights that guide engineering, research, and product decisions.

This role sits at the intersection of data, security research, and product development, helping uncover meaningful patterns in mobile telemetry, detect anomalies, and guide decision-making across the organization.

You’ll analyze structured and semi-structured datasets from millions of mobile events, build dashboards, track key performance metrics, and help our researchers identify new threat behaviors and trends across iOS and Android devices.

Your work will directly empower our security research team to focus on investigations and detection, while ensuring our engineering team builds from data-driven insights. You’ll also help translate complex telemetry into product-level intelligence, uncover trends that inform detection strategy, and surface insights that shape how iVerify evolves its threat models and platform capabilities.

As one of the foundational members of iVerify’s data function, you’ll shape our analytics stack, define best practices, and build the pipelines and dashboards that scale with the company’s growth.

• Data Exploration & Analysis: Analyze large, complex mobile telemetry datasets to identify trends, anomalies, and threat patterns.

• Dashboarding & Visualization: Build and maintain dashboards tracking platform performance, detection efficacy, and telemetry coverage.

• Research Support: Collaborate with the security research and detection teams to design data-driven experiments and surface emerging patterns of interest.

• Product Insights: Translate complex data into clear, actionable insights that inform product decisions, customer reporting, and platform improvements.

• Data Quality & Validation: Monitor the completeness and consistency of incoming data streams. Highlight quality issues and collaborate with the data engineering team to resolve them.

• Reporting & Automation: Develop repeatable reporting processes and automated queries to track key performance indicators across product and detection metrics.

• Collaboration: Work cross-functionally with engineering, machine learning, research, and customer success teams to make data accessible, explain findings, and support decisions with evidence.

• Security Analytics Enablement: Support the creation of data-driven detections and models by providing clean, validated datasets and exploratory findings.

• Use Python and the modern data science stack (Pandas, Jupyter, Num Py, Matplotlib, or equivalent) to perform deeper statistical or exploratory analysis.

• Build visualizations and dashboards in Tableau, Power BI, Looker Studio, or similar BI tools.

• Collaborate with researchers to validate hypotheses about threat activity or telemetry anomalies.

• Conduct ad hoc analyses to support product and detection improvements.

• Document key findings and communicate insights to both technical and non-technical audiences.

• Partner with data engineers to improve dataset availability, structure, and performance for analytical workloads.

• Work with…