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Digital Products Analytics Ad-Hoc Analyst

Compunnel, Inc., Plano, Texas, us, 75086

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Job Description: Texas, Plano

01/13/2026

Contract

Active

Job Summary We are seeking a Digital Products Analytics Ad-Hoc Analyst with strong experience in data analysis and visualization to support insights for digital products such as Fox.com, Fox Mobile App, and Smart TV platforms.

Key Responsibilities

Extract, transform, and load (ETL) data from various sources, ensuring data quality, integrity, and accuracy.

Perform data cleansing, validation, and preprocessing for structured and unstructured data.

Develop and execute queries, scripts, and data manipulation tasks using SQL, Python, or other relevant tools.

Analyze large datasets to identify trends, patterns, and correlations, providing actionable insights.

Create clear and concise data visualizations, dashboards, and reports for stakeholders.

Collaborate with clients and cross-functional teams to gather requirements and translate them into insights.

Support predictive modeling, machine learning, and statisticalják analysis in collaboration with Data Scientists.

Monitor data quality and proactively identify anomalies or discrepancies knj.

Stay updated on industry trends and best practices to enhance analytical techniques.

Assist in process improvements to streamline data workflows and analysis.

Required Qualifications

Minimum 1+ year of experience with Amplitude Analytics.

2–3 years of experience querying data warehouses such as Snowflake or Redshift.

Strong proficiency in SQL for writing queries, joining tables, and deriving insights.

Experience with data quality analysis (2–3 years).

Ability to create visual reports and dashboards.

Strong analytical and problem‑solving skills.

Excellent communication and organizational skills; ability to work independently and pivot quickly.

Preferred Qualifications

Experience with Python for data manipulation and automation.

Familiarity with digital product analytics and user behavior tracking.

Exposure to predictive modeling and machine learning concepts.

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