Data Analyst with 10+ years in Data Science & Project Management
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Analyst with strong foundations in Data Science, Analytics, and Data Engineering, backed by 15+ years of experience in technology, analytics-driven decision-making, and enterprise systems. Skilled in data analysis, EDA, visualization, ETL pipelines, SQL, Python, Power BI, Tableau, and statistical analysis. Adept at transforming complex datasets into actionable business insights to support strategic and operational decision-making.
IIT Bangalore & Up Grad
PGE in Data Science · Data Engineering
N/A – June 30, 2025
Wellingkars Institute
PGDM · MBA
N/A – Present
Mumbai University
B. Com
N/A – June 30, 1998
Source Page Technology PVT LTD
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June 1, 2017 – June 1, 2019
India
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Infoton System and Services PVT LTD
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June 1, 2003 – May 1, 2008
India
Project Management Professional
Unknown
June 1, 2026 – Present
Certified Oracle Database Administrator
Unknown
June 1, 2026 – Present
Oracle 9i Developer Suite: Forms6i / Reports6i
Unknown
June 1, 2026 – Present
Sun Java Programming
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse background, spanning software development, project management, and product management across various industries (finance, logistics, retail, e-commerce), suggests adaptability and a broad perspective. The recent intensive upskilling in data science indicates a strong drive for continuous learning and alignment with modern data-centric organizational cultures. The experience in leading data-driven initiatives and working with cross-functional teams points to a collaborative and results-oriented mindset.
Soft Skills & Operational Fit
The candidate's resume highlights experience in cross-functional leadership, stakeholder management, process improvement, and collaboration with product owners and Scrum teams. These indicate strong soft skills crucial for a senior data analyst role, which often involves translating technical insights for non-technical stakeholders and working within agile environments. The career break was utilized for upskilling in data science, demonstrating a proactive approach to professional growth and adaptability.