Staff Data Scientist
About the job
• Lead the design, development, and continuous improvement of advanced statistical, machine learning, and Generative AI models, focusing on talent marketplace matching, recommendation systems, and predictive analytics.
• Conduct research-driven initiatives to improve scalability, interpretability, and real-world performance of AI models to deliver measurable impact for enterprise customers.
• Build robust experimentation frameworks, including A/B testing, causal inference, and advanced statistical validation, to guide algorithmic and product decisions.
• Partner with engineering teams to ensure models are deployed efficiently, monitored effectively, and optimized for production performance.
• Collaborate closely with product managers, AI specialists, and client-facing teams to align data science initiatives with customer needs and business goals.
• Stay ahead of emerging trends in AI and GenAI, recommending innovations and best practices.
• Contribute thought leadership by publishing research, presenting at conferences, and mentoring peers.
• Serve as a technical leader and role model: low-ego servant leadership, cross-team collaboration, player-coach mentality, and business-oriented problem solving.
Requirements
- Ph.D. in a STEM discipline (Mathematics, Computer Science, Statistics, Physics, Engineering) with a significant research component.
- Strong expertise in mathematical modeling, optimization algorithms, and statistical analysis.
- Proven track record in designing, validating, and deploying machine learning and Generative AI models, ideally within marketplace or recommendation system contexts.
- Proficiency in industry-standard data science tools and frameworks (Python, TensorFlow, PyTorch, SQL) and familiarity with cloud-based data platforms.
- Ability to distill complex analytical findings into actionable insights for technical and non-technical stakeholders.
- Excellent communication and collaboration skills, with experience influencing cross-functional teams.
- Demonstrated thought leadership through publications, patents, or conference presentations is highly desirable.
