Senior Data Scientist, Product
You are confident about...
- Your ability to thrive in a fast-paced, often ambiguous work environment
- Using data to make recommendations based on your findings
- Working fast by default to produce actionable results in O(days) versus O(weeks), and slowing down when you sense elevated risk of a bad decision
- Managing timelines efficiently and communicating when deadlines are at risk
You are exceptional in your...
- Ability to leverage advanced SQL for analysis; some Python or R experience is desired
- Knowledge of statistics and experimental design (or ability to learn quickly)
- Strong intuition for consumer products, usage patterns, and funnels
- Ability to create beautiful and practical dashboards in tools such as Tableau or Hex
- Communication, interpersonal skills, and ability to establish relationships
- Attention to detail
You are enthusiastic about...
- Working cross-functionally with product managers and content leaders
- Contextualizing data to drive a deep understanding of Brilliant’s product and customers
- Working relatively autonomously in a small team to produce big results
- Deepening the “data + intuition” culture across the company
- Taking initiative, being proactive, sharing ideas, and challenging the status quo
- Partner and lead discussions with product managers to develop KPIs and inform strategy and roadmap
- Become a subject-matter expert on our product and customers, building a common understanding of how users are interacting with our product and features
- Analyze large datasets to proactively uncover trends, understand relationships, and surface actionable insights to the product team
- Approach problems using first principles, using a variety of statistical methods or ML modeling as needed to understand user behavior
- Design and analyze A/B experiments - from selecting the right metrics to interpreting results
- Build data products and analytical frameworks that accelerate and scale insights delivery
- Work with engineers to log new data sources and analytics events as we build new features
- Contribute to our data pipeline and analytics infrastructure by building curated data models in Snowflake and dbt
- We use a systematic compensation framework. Salary scales are set each year for each job vertical, based on market data and company budget. Independently, managers level folks on their team, and those levels are mapped formulaically to our compensation scales.
- Additional, we always make First and Best Offers - there is no negotiation (for new hires nor our existing teammates). This ensures that people are paid based on their expected contribution, rather than their negotiation skills.
- In San Francisco, NYC, and similar markets, the range for this role across the most likely levels for relevant candidates is $150-195k.
- We do apply a location-based adjustment in less competitive markets, typically 5-10%. Feel free to ask us about your particular location!
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