FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data analysis, machine learning engineering, and building data pipelines, with a strong focus on classification capabilities and model evaluation. Proficient in Python, SQL, and cloud environments, while effectively communicating insights to stakeholders.
Highest-signal resume keywords
Data AnalysisMachine Learning EngineeringPython ProgrammingRegular ExpressionsData Pipeline Development
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data AnalysisMachine Learning EngineeringPython ProgrammingSQLRegular ExpressionsNLP Model Fine-TuningPrecision and Recall MeasurementETL ProcessesWorkflow OrchestrationExperiment Design
Soft Skills
Problem SolvingProactive MindsetCan-Do AttitudeSelf-Starter
Tools & Technologies
SparkAirflowDagsterAWSAzureGCPGitCI/CD
Industry Keywords
CybersecurityDSPMDLPData Classification
Tech Stack
Tools & technologiesAirflowAWSAzureCloudCyber SecurityETLGoogle Cloud PlatformPythonSparkSQL
About the role
Key responsibilities & impact- Research, design, and ship new classification capabilities expanding coverage of sensitive data types
- Own the end-to-end process from research and experiments through production deployment
- Evaluate and tune regex, dictionary, fine-tuned NER, and text classification models
- Build ground truth sets and measure precision and recall
- Identify root causes of false positives and false negatives and resolve them
- Build automated evaluation and benchmark workflows to compare classifier versions and detect quality regressions
- Design, build, and maintain data pipelines and dashboards tracking classification quality and product performance
- Deliver actionable insights to stakeholders at all levels
- Support proofs of concept and customers with deep classification analysis
- Convert customer feedback into product improvements
- Participate in discussions about Sentra's AI research objectives, priorities, and solutions within the R&D Data team
Requirements
What you’ll need- 3+ years of hands-on experience in data analysis, data science or ML engineering in a B2B SaaS company
- Proficiency with Python and SQL
- Experience with Spark or similar technologies
- Strong regular expressions skills: write, test and tune patterns, and explain their false positive behavior
- Experience designing experiments and measuring model quality, including precision, recall, and error analysis
- Experience building and maintaining data pipelines, ETL processes, and workflow orchestration tools such as Airflow, Dagster, or similar
- Degree in a quantitative field such as Computer Science, Engineering, Mathematics, or Statistics
- Understanding of software development best practices, including Git, CI/CD, and testing
- Can-do attitude, problem solving skills, self-starter, proactive mindset
- Previous experience in the cybersecurity domain, DSPM, DLP, or data classification
- Experience with cloud environments such as AWS, Azure, or GCP
- Experience fine-tuning NLP models, such as NER or text classification, or using LLMs in daily work
Benefits
Comp & perks- Remote/hybrid work arrangement indicated
- Work from a Tel Aviv office near a train station