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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 regular expressions, with experience in cloud environments and cybersecurity domains.
Highest-signal resume keywords
Data AnalysisMachine Learning EngineeringPython ProgrammingRegular ExpressionsData Pipeline Development
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Data AnalysisMachine Learning EngineeringPython ProgrammingSQLRegular ExpressionsModel EvaluationData Pipeline DevelopmentETL ProcessesNLP Model Fine-TuningCloud Environments
Soft Skills
Stakeholder CommunicationProblem-SolvingCollaboration
Tools & Technologies
SparkAirflowDagsterAWSAzureGCP
Industry Keywords
B2B SaaSCybersecurityData ClassificationDSPMDLP
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 and fix root causes of false positives and false negatives
- 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
- Translate 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 (precision, recall, error analysis)
- Experience building and maintaining data pipelines, ETL processes, and workflow orchestration tools (Airflow, Dagster, or similar)
- Degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics
- Understanding of software development best practices (Git, CI/CD, testing)
- Previous experience in the cybersecurity domain (DSPM, DLP, data classification) is an advantage
- Experience with cloud environments (AWS, Azure, GCP) is an advantage
- Experience fine-tuning NLP models (for example NER or text classification) or using LLMs in daily work is an advantage
Benefits
Comp & perks- Hybrid work arrangement
- Full-time employment