Director, Data Science

This is a fully remote position, open to applicants in United States.

📋 Description

• Create and implement machine learning models aimed at applicant generation and ranking to enhance multimodal feed recommendations.

• Participate in applied ML research to elevate the quality and performance of recommendations.

• Collaborate with research, search, discovery, shopping, and engineering teams to integrate ML innovations.

• Develop personalization and exploration features to boost product metrics and user engagement.

• Design and construct both frontend and backend solutions adhering to best practices in technical design, testing, and code quality.

• Create, optimize, and revamp ML models and data pipelines for scalable first-party products and services.

• Work alongside Technical Program Managers, Data Engineers, Data Scientists, Business Analysts, and Operations teams.

• Evaluate business impacts and address system issues.

• Aid cloud engineering efforts for AI/ML training and deployment platforms.

• Integrate and implement generative AI solutions utilizing cloud-based models.

• Deploy and oversee Machine Learning and HPC systems on Google Cloud.

• Identify and validate deployment configurations to enhance performance and resource utilization.

• Design and sustain reference architectures catering to AI/ML workloads.

• Develop and roll out personalized LLMs for search and recommendation systems.

• Conduct applied research on innovative LLM techniques.

• Incorporate LLMs into various products and services.

• Execute personalized search and discovery roadmaps.

• Forge partnerships with both internal and external stakeholders for AI/ML initiatives.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Computer Information Systems, Data Science, Information Systems, Engineering, Applied Mathematics, or a related field, or an equivalent foreign degree, along with 5 years of relevant experience.

• A minimum of 3 years of experience in designing and deploying ML models specifically for financial analytics.

• At least 2 years of experience in architecting cloud-based data pipelines.

• Four years of experience in developing quantitative models for IRR, MOIC, MVOC, and WARF metrics.

• Five years of experience in implementing scalable backend systems using Java and Spring Boot.

• Four years of experience in building APIs and integrations utilizing Kafka and REST services.

• Two years of experience applying LLMs and Generative AI in document processing.

• Five years of experience with SQL and data warehousing for financial data processing and analytics.

• Five years of experience leading cross-functional AI/ML projects in collaboration with engineering and business teams.

• 100% telecommuting; candidates may reside anywhere in the US.

🏝️ Benefits

• Discretionary bonus.

• Medical benefits.

• Financial benefits.

• Additional benefits as part of the overall compensation package.