Agero, Inc. · 10 hours ago

Data Analyst

United States

Full-time

Remote

Entry, Mid Level

2+ years exp

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Responsibilities

Optimize decision-making processes across product lifecycle stages.

Conduct rigorous A/B testing and experimentation to evaluate product features, user experiences, and pricing strategies.

Analyze results to provide actionable insights that inform iterative improvements and drive conversion optimization.

Additional focus areas include analyzing product performance metrics, customer segmentation strategies, and market trends to drive informed product development and enhancement strategies.

Design and maintain real-time dashboards that monitor key performance indicators (KPIs), conducting in-depth performance analyses to identify trends, anomalies, and areas for improvement.

Provide recommendations to support both operational efficiency and strategic initiatives.

Leverage quantitative analysis and data storytelling to uncover actionable insights that drive business growth.

By deeply understanding marketplace dynamics, customer behaviors, and emerging trends, you will empower business and product leaders to make data-driven decisions.

Translate complex data into clear, compelling narratives that inspire innovation and continuous improvement.

Partner effectively with teams across Product Management, Engineering, Marketing, Sales, and other departments to prioritize and execute data-driven projects.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data AnalyticsSQLPythonRData VisualizationCloud Data PlatformsStatistical TechniquesA/B TestingRegressionTableauPowerBISigmaGBQSnowflakeRedshiftProject Management

Required

Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a related technical field.

2-4 years of experience in data analytics, business analytics, consulting, or related roles.

Experience with cloud data platforms such as GBQ, Snowflake, or Redshift.

Proficiency in querying, analyzing, and visualizing large datasets using SQL, Python, R, and data visualization tools (e.g., Sigma, Tableau, PowerBI).

Strong understanding of statistical techniques (e.g., Regression, A/B Testing, Causal Inference) and their application in business contexts.

Excellent communication and presentation skills, with the ability to convey complex data insights to non-technical stakeholders.

Strong analytical and problem-solving skills, capable of translating business requirements into actionable analytical solutions.

Demonstrated ability in project and task management, attention to detail, and the ability to work independently, as well as part of a team.