Data science Team Lead

We offer the industrys only platform that fuses customer identity and anti-fraud solutions customer identity management identity verification and fraud prevention.

We sell to industries with large consumer-facing businesses such as: banking financial services insurance fintech gaming ecommerce/retail telco / media utilities etc.

About the Role:

Transmit Security is building the next generation of fraud prevention and Detection & Response capabilities powered by advanced machine learning and real-time decisioning.

As the Data Science Team Lead you will lead a talented team of data scientists and ML engineers building the infrastructure systems and workflows for designing training evaluating and deploying machine learning models that protect millions of users worldwide from fraud and account compromise.

This role combines hands-on technical leadership with people management and strategic ownership. You will drive innovation across real-time model serving customer-specific model tuning offline AI evaluations and scalable ML systems in a production-grade SaaS environment.

If you are passionate about applied machine learning fraud detection and building intelligent systems at scale - we want you on our team.

What youll do:

• Lead and mentor a team of Data Scientists and ML Engineers focused on fraud detection and response capabilities.
• Build ML infrastructure focused on design train evaluate and optimize machine learning models for real-time fraud prevention and risk assessment.
• Own the lifecycle of ML models in production including experimentation deployment monitoring retraining and performance optimization.
• Drive customer-specific model training and tuning strategies to improve accuracy and adaptability across different customer environments.
• Build and improve offline AI evaluation frameworks to measure model quality drift effectiveness and business impact.
• Collaborate closely with Engineering Product Security and Data teams to deliver scalable and reliable AI-powered capabilities.
• Define best practices for model serving feature engineering experimentation observability and operational excellence.
• Balance model performance latency scalability explainability and operational constraints in high-scale production environments.
• Promote a culture of technical excellence continuous improvement ownership and innovation.

What youll need:

• 5 years of experience in Data Science Machine Learning or Applied AI roles with at least 2 years in a leadership capacity.
• Strong hands-on experience building and deploying ML models in production environments.
• Experience with real-time inference/model serving architectures and low-latency prediction systems.
• Deep understanding of model training evaluation tuning and monitoring methodologies.
• Experience designing customer-specific ML solutions and personalization strategies.
• Strong programming skills in Python and experience with modern ML frameworks and tooling.
• Proven ability to lead technical initiatives and guide teams in fast-paced production-focused environments.
• Strong analytical and problem-solving skills with a data-driven mindset.
• Excellent communication and cross-functional collaboration skills.

Advantages:

• Experience with fraud detection identity risk cybersecurity or behavioral analytics systems.
• Experience with MLOps practices and tooling.
• Background in Data Engineering and large-scale data processing systems.
• Experience with feature stores stream processing and real-time data pipelines.
• Familiarity with cloud platforms such as AWS GCP or Azure.
• Experience with Kubernetes Kafka Spark Airflow or similar distributed systems technologies.
• Bachelors degree in Computer Science Mathematics Statistics Engineering or a related field

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