Programmer Analyst with 1+ years in Data Analysis & BI
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Experienced Programmer Analyst Trainee with 1.3 years of hands-on experience in data analysis, business intelligence, and programming. Proficient in SQL, Python, Excel, and PowerBI, with a proven track record of optimizing data processes, improving revenue recovery, and automating reporting pipelines. Skilled in root cause analysis, stakeholder communication, and developing actionable insights from complex datasets.
AISSMS Institute of Information Technology
Bachelor of Engineering · Artificial Intelligence and Data Science
February 1, 2021 – May 1, 2025
Cognizant
Programmer Analyst Trainee
March 1, 2025 – Present
Pune, Maharashtra, India
iMocha
Business Analyst Intern
August 1, 2024 – March 1, 2025
Pune, Maharashtra, India
Pricing & Promotion Effectiveness Analysis
June 17, 2026 – Present
Uncovered $2.1M in wasted promotional spend by analyzing 2.8M retail transactions across 30 campaigns found that 17% of campaigns generated zero incremental demand due to pantry loading (customers stocked up during promo, stopped buying after). Proved that discounts beyond 20% destroy margin, the 30%+ discount band showed, 64% revenue loss, while the 1-10% band delivered 36% sales lift, directly leading to a recommendation to cap all promotions at 15%. Discovered display promotions deliver 3x higher ROI than mailers (0.14x vs -0.04x), yet 60% of budget was allocated to mailers, recommended budget reallocation projected to triple promotional returns. Segmented 801 households using RFM analysis and K-Means clustering, revealed that high value customers don't need discounts (+0.34% lift), while at-risk customers don't respond to them (-0.37%), eliminating wasteful blanket discounting. Built complete analytics infrastructure: dbt pipeline (14 models, 28 tests) on Snowflake, statistical validation in Python (t-tests, DiD, K-Means), interactive Power BI dashboard with What-If simulation, and Excel ROI calculator for marketing team to model scenarios before launching campaigns.
View ProjectAPI-Augmented Reinforcement Learning Framework
June 17, 2026 – Present
Built an API-driven reinforcement learning framework that optimized portfolio allocation across 50+ stocks improved risk adjusted returns by 15% compared to baseline buy and hold strategy. Ran sentiment analysis on 1,000+ financial news articles using NLP, converting unstructured text into quantifiable market signals that fed directly into the portfolio decision engine. Combined sentiment scores with historical price data to create a hybrid model that outperformed pure technical analysis, the sentiment layer alone accounted for 8% of the total return improvement.
View ProjectCultural Fit Analysis
The candidate's projects and experience show a strong inclination towards data-driven decision-making and process optimization, which aligns well with roles requiring analytical rigor. Their academic background in AI and Data Science, coupled with practical application in business analysis and programming, indicates a versatile and adaptable individual. The diversity of projects (retail analytics, financial modeling, HR analytics, healthcare claims) suggests a broad interest and ability to apply skills across different domains, contributing positively to cultural fit in a dynamic environment. However, the experience level is relatively junior, which might require mentorship in a senior role.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving abilities, attention to detail, and a results-oriented approach, as seen in their ability to identify and resolve significant issues leading to tangible financial and efficiency improvements. Their experience in automating manual processes and designing reporting tools indicates a proactive and efficient operational mindset. The candidate's ability to present findings and recommendations to leadership suggests good communication and stakeholder management skills.