Director, Data Science

TWG Global

. Develop and deploy machine learning models for applicant generation and ranking to enhance multimodal feed recommendations .

Posted 10/21/2026full-timeRemote • United StatesLead💰 $139,818 - $360,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying machine learning models, particularly for financial analytics, while integrating cloud-based solutions and optimizing data pipelines. Proven ability to lead cross-functional AI/ML projects and enhance product metrics through innovative personalization techniques.

Highest-signal resume keywords

Machine Learning Model DevelopmentCloud-Based Data Pipeline ArchitectureJava and Spring Boot Backend DevelopmentSQL and Data Warehousing for Financial AnalyticsGenerative AI and LLM Integration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData Pipeline ArchitectureJavaSpring BootSQLAPIsKafkaREST ServicesGenerative AILLMs

Soft Skills

CollaborationProblem SolvingCross-Functional Leadership

Tools & Technologies

Google CloudHPC Systems

Industry Keywords

Financial AnalyticsRecommendation SystemsPersonalizationApplied ResearchData Processing

Tech Stack

Tools & technologies

CloudJavaKafkaSpringSpring BootSpringBootSQL

About the role

Key responsibilities & impact

Develop and deploy machine learning models for applicant generation and ranking to enhance multimodal feed recommendations
Engage in applied ML research to improve recommendation quality and performance
Integrate ML innovations with research, search, discovery, shopping, and engineering teams
Implement personalization and exploration features to improve product metrics and user engagement
Design and develop frontend and backend solutions following technical design, testing, and code quality best practices
Develop, optimize, and redesign ML models and data pipelines for scalable first-party products and services
Collaborate with Technical Program Managers, Data Engineers, Data Scientists, Business Analysts, and Operations
Analyze business impacts and resolve system issues
Support cloud engineering initiatives for AI/ML training and deployment platforms
Integrate and deploy generative AI solutions using cloud-based models
Deploy and manage Machine Learning and HPC systems on Google Cloud
Identify and validate deployment configurations to optimize performance and resource utilization
Design and maintain reference architectures for AI/ML workloads
Develop and deploy personalized LLMs for search and recommendation systems
Conduct applied research on emerging LLM techniques
Integrate LLMs into products and services
Execute search and discovery personalization roadmaps
Establish partnerships with internal and external stakeholders for AI/ML initiatives

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Computer Information Systems, Data Science, Information Systems, Engineering, Applied Mathematics, or related field, or foreign equivalent degree plus 5 years of related experience
3 years of experience designing and deploying ML models for financial analytics
2 years of experience architecting cloud-based data pipelines
4 years of experience developing quantitative models for IRR, MOIC, MVOC, and WARF metrics
5 years of experience implementing scalable backend systems using Java and Spring Boot
4 years of experience building APIs and integrations using Kafka and REST services
2 years of experience applying LLMs and Generative AI for documents
5 years of experience utilizing SQL and data warehousing for financial data processing and analytics
5 years of experience leading cross-functional AI/ML projects with engineering and business teams
100% telecommuting; can reside anywhere in the US

Benefits

Comp & perks

Discretionary bonus
Medical benefits
Financial benefits
Other benefits as part of the compensation package