Efrat Margalit Klyman
About Efrat Margalit Klyman
Efrat Margalit Klyman is the Professional Services Team Lead at Earnix, where she has worked since 2023. She has extensive experience in data analysis and programming, having held various roles at companies such as Citi and Bioforum Ltd.
Work at Earnix
Efrat Margalit Klyman has been serving as the Professional Services Team Lead at Earnix since 2023. In this role, she is responsible for leading a team that focuses on delivering professional services to clients, ensuring that their needs are met effectively. Her position involves leveraging her extensive background in data analysis and programming to provide actionable insights and solutions.
Previous Experience in Data Analysis
Before joining Earnix, Efrat held several positions in data analysis. She worked at Citi as a Data Analyst from 2020 to 2021, and later as a Data Analyst Team Lead from 2021 to 2023. Her experience also includes roles at G-STAT as a Marketing Data Analyst and at Paretix as a Data Analyst. Additionally, she briefly served as a Senior Data Analyst at Citi in 2021.
Education and Expertise
Efrat holds a Bachelor's degree in Economics and Statistics and a Master's degree in Statistics, both from The Hebrew University of Jerusalem. She also completed a Data Analysis Professional course at NAYA-College and studied Python at She Codes. Her educational background equips her with strong analytical and problem-solving skills, which she applies in her professional roles.
Leadership and Management Skills
Efrat possesses strong leadership and people management skills, developed during her time as a former army lieutenant. These skills enhance her ability to lead teams effectively and manage projects in high-pressure environments. Her proactive approach and attention to detail contribute to her success in her current role and previous positions.
Technical Skills and Programming Knowledge
Efrat has cross-functional experience in various programming languages and tools, including Excel, SQL, R, and SAS. Her technical skills enable her to analyze complex datasets and turn raw data into actionable business insights. She is known for being a fast learner, which aids her in adapting to new technologies and methodologies in data analysis.