Data Science Team Lead
Posted 2 days ago · 0 applicants
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The role in plain words
This role is for a Data Science Team Lead who will directly manage a team of 3 Data Scientists while spending about 30–40% of their time hands-on. Responsibilities include leading applied ML research for fraud detection and identity verification, as well as driving the engineering lifecycle, infrastructure, and real-time production monitoring.
- 5+ years of hands-on experience in Data Science / Applied Machine Learning roles
- 2+ years of direct team management / leadership experience
- Proficiency in Python for Data Science and Machine Learning
- Hands-on experience taking Machine Learning models to Production (MLOps, Scalability, Monitoring)
- Experience with Big Data and ML frameworks (Spark, Airflow, Cloud environments)
Extracted from the job description · kept up to date automatically
Who this suits
This position suits experienced Data Scientists with at least 5 years of hands-on ML experience and 2+ years of direct team leadership who are skilled in Python and MLOps. It may be less ideal for those seeking a purely hands-on role or individuals without prior management experience.
Full job description
Original listing · kept for referenceA highly profitable Cyber Security & FinTech Unicorn developing an enterprise SaaS identity verification and biometric authentication platform.
The solution enables seamless integration of advanced multi-factor authentication (facial recognition, fingerprint, voice analysis) and fraud prevention across high-scale applications.
Serving top-tier global financial institutions, banks, and major insurance corporations.
The company operates internationally with several hundred employees, with roughly half based in its primary Israeli R&D hub.
Located in central Tel Aviv (walking distance from the train station), operating on a hybrid work model with 2 days WFH per week.
Role Description-
• Joining as Data Science Team Lead, directly managing 3 Data Scientists with ~30–40% hands-on orientation, reporting to the Group Manager.
• Leading applied ML research: model selection, optimizing Decision Trees, feature engineering, training, and evaluation for Fraud Detection and identity verification algorithms.
• Driving the engineering lifecycle: building enterprise-grade DS/ML infrastructure, real-time production monitoring, and ensuring overall scalability.
• End-to-end responsibility across the full DS/MLOps lifecycle, working closely with Airflow, Spark, Cloud ecosystems, and production deployment tools.
Requirements-
• 5+ years of hands-on experience in Data Science / Applied Machine Learning roles – Mandatory
• 2+ years of direct team management / leadership experience – Mandatory
• Proven proficiency in Python for Data Science and Machine Learning – Mandatory
• Hands-on experience taking Machine Learning models to Production (MLOps, Scalability, Monitoring) – Mandatory
• Experience with Big Data and ML frameworks (Spark, Airflow, Cloud environments) – Advantage
• Background or domain knowledge in Fraud Detection, Cybersecurity, or Biometrics – Advantage
154504
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- Hybrid
- 5+ years of hands-on experience in Data Science / Applied Machine Learning roles, 2+ years of direct team management / leadership experience, Proficiency in Python for Data Science and Machine Learning, Hands-on experience taking Machine Learning models to Production (MLOps, Scalability, Monitoring)