Junior Data Analyst
DRS RADA Technologies
- Where
- Netanya, Israel, on-site
- Language, from the listing
- No Hebrew mentionedA missing mention doesn't mean Hebrew isn't needed. Ask if it matters to you.
- Dates
- Found 9 Oct 2026
- Last checked on the employer's site
- 2 h ago (9 Oct 2026)
- Source
- Employer career page (Comeet)
What they ask for
- Bachelor's degree in data engineering, Statistics, or a related field
- Full-time availability
- Experience with statistical analysis and experimental design.
- Ability to quickly learn new data tools.
- Ability to identify patterns, trends, and outliers in data.
- Exceptional attention to detail in data analysis and reporting.
- Enthusiastic about data with a strong interest in exploring and analyzing large-scale datasets
Nice to have
- Proficiency in data analysis tools and languages (Python, Advantage- pyspark, Pandas, Plotly, SQL).
- Experience working with big data technologies, preferably Databricks (an advantage).
- Familiarity with radar signal processing (an advantage).
The full listing
Description
DRS RADA is a global pioneer of RADAR systems for active military protection, counter-drone applications, critical infrastructure protection, and border surveillance.
We are looking for a B.Sc. with analytical capabilities to be part of a Data Engineering team.
Key Responsibilities:
• Data Collection
• Develop and maintain data analysis and tagging tools.
• Collaborate with cross-functional teams to collect experiments.
• Experiments Analysis
• Analyze and tag field experiments.
• R&D Data Analysis Support
• Analyze datasets to extract meaningful data-based insights.
Requirements
Requirements:
• Bachelor's degree in data engineering, Statistics, or a related field
• Full-time availability
Skills:
• Proficiency in data analysis tools and languages (Python, Advantage- pyspark, Pandas, Plotly, SQL).
• Experience working with big data technologies, preferably Databricks (an advantage).
• Familiarity with radar signal processing (an advantage).
• Experience with statistical analysis and experimental design.
• Ability to quickly learn new data tools.
• Ability to identify patterns, trends, and outliers in data.
• Exceptional attention to detail in data analysis and reporting.
• Enthusiastic about data with a strong interest in exploring and analyzing large-scale datasets