Data Scientist

Lusha

Data Scientist building AI-first personalization and production ML models for Lusha's sales platform. Developing agentic pipelines and data-driven experiences that improve engagement, revenue, and retention.

Posted 8/24/2026full-timeTel Aviv • 🇮🇱 IsraelMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying end-to-end machine learning models, with a strong focus on building personalized user experiences and robust ML pipelines. Holds an advanced degree in a quantitative field and possesses proficiency in Python and AI development tools.

Highest-signal resume keywords

Data Science ExperienceMachine Learning Model DeploymentPython ProficiencyNatural Language Processing (NLP)Agentic Flow Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData ScienceTabular Data AnalysisTime Series AnalysisML Pipeline DevelopmentPythonSparkPandasNumPySciPy

Soft Skills

CollaborationAdaptabilityProblem Solving

Tools & Technologies

Scikit-learnCursorClaude CodeDatabricks

Certifications & Qualifications

MScPhD

Industry Keywords

Big DataAI DevelopmentUser ExperienceBusiness MetricsData-Driven Solutions

Tech Stack

Tools & technologies

NumpyPandasPythonScikit-LearnSpark

About the role

Key responsibilities & impact

Design and deploy end-to-end machine learning models that move business metrics
Build AI-first features that personalize the sales experience
Develop robust and efficient agentic pipelines
Collaborate with ML engineers, product managers, data engineers, and business stakeholders
Define and prioritize business problems addressed through Data Science and machine learning pipelines
Build personalized, data-driven user experiences that improve engagement, revenue, and retention
Own solutions end to end, from defining success criteria through monitoring and maintenance
Participate in weekly sessions to share research, test new ideas, and learn with the team

Requirements

What you’ll need

3-5 years of hands-on Data Science experience, including developing ML systems
MSc or PhD in a relevant quantitative field (e.g., Computer Science, Statistics, Applied Math, Physics, Engineering) with a thesis
Proficiency with Python (Spark, Pandas, NumPy, SciPy, scikit-learn)
Strong technical aptitude with the ability to quickly learn and adapt to new frameworks, tools, and systems
Proven experience with tabular data, time series analysis, and building robust, scalable ML pipelines
Experience with text-based data and NLP - Must
Experience with agentic flow development - Must
Proven track record of deploying end-to-end ML models into production - Must
Experience using AI development tools such as Cursor or Claude Code - Must
Experience training models for adaptive or individualized user experiences (nice to have)
Experience with Big Data technologies such as Spark and Databricks (nice to have)

Benefits

Comp & perks

Hybrid work model with 3 days a week in the office
Weekly team sessions for research sharing, testing new ideas, and learning together