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Open nowPosted 178 days ago

Data Science Team Lead

Transmit Security11 open roles

Where
Tel Aviv-Yafo, Gush Dan, Israel
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Your applicationOpen nowData Science Team LeadTransmit Security · Tel Aviv-Yafo, Gush Dan, Israel

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Transmit Security's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

13.8% of postings close within 7 days. Measured by our own scanner across the market. Transmit Security postings stay open a median of 37 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.8%7 days
  4. 22.3%14 days
  5. 37.8%30 days
  6. 59.0%60 days
This job: posted 178 days ago

Transmit Security median: 37 days open

The posting

Company Overview:

Transmit Security protects large enterprises from fraud and identity attacks. Our platform spans Mosaic (SaaS identity and fraud orchestration), FlexID (on-prem IAM), standalone fraud prevention and detection, and Agentic Trust, which secures AI agents that act on behalf of customers. Our technology is recognized by analysts, and our buyers are CISOs, fraud and financial crime leaders, and identity and digital channel owners. The product is ahead of the brand.

Position Overview:

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 We Look for in Candidates:

  • Lead and mentor a team of Data Scientists 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.

Ideal Candidate Profile:

  • 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.
  • Bachelor’s degree in Computer Science, Mathematics, Statistics, Engineering, or a related field.

Core Values:

  • Integrity: Ethical and transparent approach in all interactions.
  • Entrepreneurial Spirit: Treats the role as a business owner, taking initiative and ownership.
  • Resilience & Growth Mindset: Maintains drive through setbacks, continuously learning and evolving.
  • Collaboration: Strong ability to work cross-functionally with internal teams (SE, Marketing, Legal, etc.) and externally with customers.
  • Customer-Centric: Prioritizes customer relationships and continuously seeks to understand and meet their evolving needs.
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