Drive innovation at Clio as a Data Scientist focused on architectural leadership for machine learning. This hybrid position offers a unique prospect to design scalable forecasting systems.

Clio seeks a Data Scientist with over eight years of experience to establish architectural standards for ML systems while owning the development of complex models. You will influence the company's data strategy, integrate advanced statistical methodologies, and mentor junior Data Scientists, ensuring high-quality outputs.

The role involves collaborating with Data Engineering to streamline data access for machine learning applications.

Key Responsibilities:
Define the architectural roadmap for the company’s forecasting needs
Architect scalable frameworks for ML and data systems




Lead high-impact model development with a focus on deep learning
Establish CI/CD standards and conduct code audits
Integrate causal inference for comprehensive global forecasts

Requirements:
8+ years in Data Science or a quantitative field
Expertise in Python, SQL, AWS, and distributed computing
Master’s or PhD in relevant quantitative domains
Exceptional communication skills for stakeholder engagement
Proven ability to influence and drive technical vision

Utilize your leadership skills to shape Clio's machine learning future.
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