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Data Scientist with less than a year in Data Analysis & Business Intelligence
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Jeune ingénieure spécialisée en ERP et Business Intelligence, passionnée par l'analyse de données, la visualisation et l'automatisation. Capable d'analyser des données complexes et de les transformer en informations exploitables pour la prise de décision. Je suis actuellement à la recherche d'un poste de Data Analyst.
ESPRIT - ÉCOLE D'INGÉNIERIE
Ingénieure · ERP & Business Intelligence
August 1, 2020 – June 30, 2025
BEECODERS
PROJET DE FIN D'ÉTUDES
January 1, 2025 – December 31, 2025
India
BH BANK
ANALYSTE DE DONNÉES RH
July 1, 2024 – October 31, 2024
India
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Cultural Fit Analysis
The candidate's academic background in ERP & Business Intelligence, coupled with diverse project experiences (financial prediction, HR analytics, sports data, sales forecasting, sentiment analysis), indicates a broad interest in applying data science across various domains. This versatility suggests adaptability and a willingness to tackle different business challenges, which is a positive for cultural fit in dynamic environments. The pursuit of multiple certifications also shows a self-driven and continuous learning mindset, aligning with cultures that value growth and initiative. The target role 'Data Scientist Data Scientist' aligns with the candidate's demonstrated skills and interests, although the experience level is still junior.
Soft Skills & Operational Fit
The candidate demonstrates a proactive attitude towards learning and skill development, as evidenced by numerous certifications. Project descriptions highlight problem-solving abilities and a results-oriented approach (e.g., '+30% de précision', 'réduisant 50h/semaine'). Experience with Agile Scrum suggests familiarity with collaborative development methodologies. The candidate's profile indicates a passion for data analysis, visualization, and automation, which aligns well with operational roles requiring continuous improvement and data-driven decision-making.