As a Senior Data Scientist on our Applied AI team, you will join our Tel Aviv office and play a hands-on, end-to-end role in delivering innovative capabilities that help mayors and other city leaders understand their communities and improve the lives of millions worldwide. Reporting to the Applied AI Team Lead, you will collaborate with product, engineering, and fellow data-science teammates to turn cutting-edge research into production-ready solutions-quickly, reliably, and with maximum real-world impact. Youll work with a rich mix of data sources (including social media, news stories, survey results, resident feedback, and more) to create models and AI-powered features that scale.
Day to Day
Design, build, and deploy AI and machine-learning solutions, from data exploration through modeling, evaluation, and integration into customer-facing products and internal tools.
Optimize models for quality and scalability through feature engineering, hyper-parameter tuning, runtime profiling, and thoughtful architectural choices.
Build and maintain data pipelines using tools such as Airflow, Spark, and Databricks to ensure clean, reliable inputs for downstream models.
Collaborate closely with product managers, engineers, and designers to refine problem statements, iterate rapidly, and ship impactful features on schedule.
Champion technical excellence by conducting code reviews, sharing best practices, and mentoring teammates across data science and engineering.
Stay current with the latest developments in AI-including LLMs, RAG systems, and AI agents-and proactively propose ways to incorporate new techniques into our workflows.
Work an in-person or hybrid schedule, spending at least three days per week in our Tel Aviv office.
Requirements: 5 + years of hands-on experience developing and deploying machine-learning or data-science solutions with Python and SQL.
Ability to deliver production-ready NLP systems, leveraging expertise in classical NLP methods (e.g., TF-IDF/CRF, topic modeling) and modern LLMs (e.g., prompting, RAG, fine-tuning)
Proven, end-to-end experience building AI- and machine learning-based solutions from prototype to production deployment.
Demonstrated success shipping data-intensive services to production on cloud infrastructure using data tools such as PostgreSQL, Databricks, Spark, or Airflow.
Deep understanding of machine-learning fundamentals in theory and practice
Expertise in machine learning metrics and quality control.
Solid understanding of software-engineering best practices (including design patterns, data structures, and version control).
Excellent interpersonal and communication skills, with the ability to explain complex technical concepts to non-technical stakeholders and collaborate across teams.
This position is open to all candidates.