Scientist Jobs

About The Position

Requirements

• 5+ years of experience in data science, applied statistics, or analytics, preferably in a product or business analytics role.
• Solid understanding of experimental design and statistical analysis, with the judgment to know when and how to apply them.
• Strong SQL skills and proficiency in Python or R for analysis and modeling.
• Experience architecting and maintaining data pipelines using modern cloud data science workflows (e.g., Git, Databricks, Python, AWS, Azure, or equivalent).
• Experience working with large-scale product datasets and behavioral event data.
• Strong business intuition and the ability to connect metrics to real-world user experiences and broader business outcomes.
• Demonstrated ability to communicate complex analyses, trade-offs, and recommendations to both technical and senior non-technical audiences.
• Experience with Adobe Analytics or similar web/product analytics tools.
• A track record of mentoring or providing technical direction to junior team members.
• BS, MS, or PhD or equivalent experience in a quantitative field (e.g., Statistics, Computer Science, Economics, Engineering); Master's degree preferred.

Responsibilities

• Own analytics for a defined area within Firefly end-to-end, from metric definition through reporting, insight generation, and stakeholder communication.
• Independently translate ambiguous product and business questions into structured analytical approaches with minimal guidance.
• Identify patterns, trends, and relationships across datasets that surface new insights and directly influence product direction and business outcomes.
• Conduct sound statistical analysis, recognizing errors, biases, and trade-offs within the business context; contribute to experimentation and testing where relevant to your area.
• Partner with Product, Engineering, Design, and Marketing to define success metrics and guardrails aligned with user value and business goals.
• Communicate and synthesize complex analyses into clear, actionable narratives for both technical and senior business stakeholders, with limited supervision.
• Architect, build, and improve scalable self-serve dashboards, pipelines, and analytics tools that support your area and the broader organization.
• Proactively identify data quality issues, logging gaps, and infrastructure needs, and drive resolution together with data engineering partners.
• Mentor and provide technical guidance to junior data scientists; may contribute to technical interviewing and hiring decisions.
• Take ownership of one or more technical projects from start to finish, and summarize progress, trade-offs, and recommendations to management.

Benefits

• comprehensive benefits programs