Abhiram Indrala
Data & Business Analyst
About
Analytical and detail-oriented Data & Business Analyst with a B.Sc. in Statistics & Data Science (2024) and 10 months of full-time experience at NIT Skills India Pvt Ltd. Skilled in MIS reporting, SQL, Python, Power BI, Tableau, and Advanced Excel. Proven ability to design dashboards, track KPIs, conduct market/competitor analysis, and deliver actionable insights. Experienced in leveraging AI tools (ChatGPT, Claude, Copilot) for automation and reporting. Open to remote and on-site roles across India, with relocation flexibility.
Skills & Expertise (24)
Work Experience
Data Analyst
NIT Skills India Pvt Ltd
Oct 2025 - Aug 2026
Prepared and maintained MIS reports and dashboards for sales, conversions, and inventory. Automated reporting workflows using SQL + Python + AI tools, reducing manual effort by 20%. Conducted competitor benchmarking and KPI analysis to identify operational improvement opportunities. Collaborated with stakeholders to clarify requirements and deliver actionable insights.
Data Science Intern
Multiple Programs (Teachnook, Bharat Intern, Digital Bhem, Technohacks, Oasis Infobyte)
Aug 2024 - Apr 2025
Conducted market and competitor analysis to support project strategies. Built dashboards to track KPIs for HR, customer behavior, and campaign performance. Leveraged AI tools to classify data and generate commentary on metric movements. Documented workflows and collaborated with teams to ensure consistent delivery.
Education
B.Sc. in Statistics & Data Science - Giriraj Govt. Degree College
- 2024 · Afghanistan
Certifications
Data Science With Python
Teachnook · 2024
Data Science with Python – Teachnook Certification Completed a structured certification program covering Python programming, data handling, visualization, and machine learning fundamentals. The course emphasized: Python foundations (data types, control flow, functions, modules) Data analysis with NumPy & Pandas (cleaning, transformation, aggregation) Visualization (Matplotlib, Seaborn for insights and reporting) Machine Learning basics (supervised & unsupervised models using scikit‑learn) Hands‑on projects applying Python to real datasets for anomaly detection, KPI monitoring, and predictive analysis
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Skills (24)
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