Note: The job is a remote job and is open to candidates in USA. Brilliant® is seeking a Staff Data Scientist who will be a senior individual contributor responsible for advanced data analysis and research. This role focuses on understanding data deeply and translating analytical findings into recommendations that inform product, engineering, and business decisions.
Responsibilities
- Explore large, complex datasets to uncover patterns, anomalies, and opportunities
- Design and evaluate statistical and machine learning models to support insight discovery and hypothesis testing
- Partner with product, engineering, and business stakeholders to frame questions and translate findings into actionable insights
- Conduct feature exploration and selection to inform downstream AI and analytics initiatives
- Design experiments and analyses to validate assumptions and measure impact
- Develop prototypes and proofs of concept that demonstrate the potential value of new models or approaches
- Communicate results clearly through narratives, visualizations, and written recommendations
- Stay current with advances in data science, statistics, and applied machine learning
- Collaborate with Data Engineering and AI Engineering teams to transition validated ideas into production-ready work
- Mentor other data scientists and analysts, raising the level of analytical rigor across the organization
Skills
- 10+ years of experience in data science, applied research, or advanced analytics roles
- Strong foundation in statistics, probability, and experimental design
- Experience designing and evaluating machine learning models for classification, regression, clustering, or forecasting
- Proficiency in Python and common data science libraries
- Experience working with large datasets in SQL-based and analytical data environments
- Ability to reason about data quality, bias, and limitations
- Proven ability to work in ambiguous problem spaces and define meaningful analytical questions
- Strong communication skills, able to explain complex findings to non-technical audiences
- Experience influencing product or business strategy through data-driven insights
- Comfortable collaborating across disciplines without formal authority
- Structured thinker who can balance exploration with rigor
- Deep curiosity and a passion for discovery
- Belief that insights precede automation and that not every problem needs a model
- Learning-first attitude, continuously improving methods and tools
- Pragmatic and outcome-oriented, focused on decisions and impact
- Respects the difference between research, engineering, and operations while collaborating closely with all three
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