Data Science Team Lead
We are seeking a Data Science Team Lead with expertise in banking/fintech to lead a high-performing DS team. This position combines advanced ML knowledge, team leadership, and cross-functional collaboration to drive data-driven solutions in scorecard development, portfolio risk management, and model performance monitoring.
Key Responsibilities:
Advanced ML Development and Deployment:
Build and refine ML models for credit scoring, fraud detection, marketing strategies, and customer behavior analytics.
Manage AI initiatives, including integrating external AI services.
Oversee the lifecycle of ML models, from concept to deployment, including quality assurance, recalibration, and performance monitoring.
Team and Stakeholder Management:
Lead and develop the DS team through hiring, training, and performance management.
Collaborate with risk, collection, and business teams to align DS projects with organizational needs.
Facilitate communication and prioritize tasks to meet stakeholder expectations.
Process and Tool Optimization:
Manage tools and processes such as Git, Jira, Confluence, and Agile workflows.
Ensure data reliability and stability through collaboration with DWH teams and feature-store administration.
Drive integration and optimization of new and existing data sources.
Knowledge and Standards Management:
Maintain comprehensive project documentation and implement best practices.
Oversee knowledge-sharing initiatives, including Confluence updates, Git documentation, and internal training.
Stay ahead of industry trends and methodologies, introducing innovative tools and processes.
Requirements
Technical: Python, SQL, ML techniques (regression, classification, boosting, NLP/LLM)
Tools: PowerBI, Excel, Tableau, Git, AWS (preferred), MLOps experience
Soft Skills: Team leadership, excellent communication, agile expertise, and risk analytics experience (preferred)
Language: Fluent English
Preferred Qualifications:
Educational background in mathematics, machine learning, or statistics
Proven experience in fintech and banking, particularly in emerging markets
Experience with AI-tools
Expertise in ML for text, speech, and behavioral analytics or dynamic models in the card business.
Benefits
Flexible and completely remote full-time role
The opportunity to work in an innovative fintech company with a global reach
Engaging tasks and the chance to influence the development of cutting-edge products
The opportunity to grow your skills in a global, distributed team environment.
Apply Now
Key Responsibilities:
Advanced ML Development and Deployment:
Build and refine ML models for credit scoring, fraud detection, marketing strategies, and customer behavior analytics.
Manage AI initiatives, including integrating external AI services.
Oversee the lifecycle of ML models, from concept to deployment, including quality assurance, recalibration, and performance monitoring.
Team and Stakeholder Management:
Lead and develop the DS team through hiring, training, and performance management.
Collaborate with risk, collection, and business teams to align DS projects with organizational needs.
Facilitate communication and prioritize tasks to meet stakeholder expectations.
Process and Tool Optimization:
Manage tools and processes such as Git, Jira, Confluence, and Agile workflows.
Ensure data reliability and stability through collaboration with DWH teams and feature-store administration.
Drive integration and optimization of new and existing data sources.
Knowledge and Standards Management:
Maintain comprehensive project documentation and implement best practices.
Oversee knowledge-sharing initiatives, including Confluence updates, Git documentation, and internal training.
Stay ahead of industry trends and methodologies, introducing innovative tools and processes.
Requirements
Technical: Python, SQL, ML techniques (regression, classification, boosting, NLP/LLM)
Tools: PowerBI, Excel, Tableau, Git, AWS (preferred), MLOps experience
Soft Skills: Team leadership, excellent communication, agile expertise, and risk analytics experience (preferred)
Language: Fluent English
Preferred Qualifications:
Educational background in mathematics, machine learning, or statistics
Proven experience in fintech and banking, particularly in emerging markets
Experience with AI-tools
Expertise in ML for text, speech, and behavioral analytics or dynamic models in the card business.
Benefits
Flexible and completely remote full-time role
The opportunity to work in an innovative fintech company with a global reach
Engaging tasks and the chance to influence the development of cutting-edge products
The opportunity to grow your skills in a global, distributed team environment.
Apply Now