Help & Supportcareers@gravityer.com
Data Science with less than a year in Python, SQL, and Power BI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Shubham Dubey is an aspiring Data Science professional currently pursuing a Master of Computer Applications. He possesses strong skills in Python (Pandas, NumPy, Scikit-learn, Prophet), SQL, and Power BI, with hands-on experience in data analysis, EDA, sentiment classification, and time-series forecasting. His project portfolio demonstrates the ability to develop data-driven solutions and interactive dashboards for placement management, social media intelligence, and retail sales forecasting, aiming to deliver actionable insights and improve operational efficiency.
Bharati Vidyapeeth Institute of Computer Applications and Management (GGSIPU)
Master of Computer Applications
August 1, 2024 – Present
University of Allahabad
Bachelor of Science
August 1, 2019 – June 30, 2022
Placement Management Module
June 1, 2026 – Present
Performed data analysis and EDA on 200+ student records and 20+ company profiles to design a centralized placement system. Implemented role-based access control reducing unauthorized data exposure by ~30% and shortlisting efficiency by ~40%. Developed Power BI dashboard to monitor key metrics such as application status and trends.
Social Media Sentiment & Brand Intelligence Dashboard
June 1, 2026 – Present
Collected and preprocessed 25,000+ tweets/Reddit posts across 3 brand competitors; cleaned noise (emojis, URLs, hashtags) via regex pipelines. Applied VADER & TextBlob for sentiment classification achieving 82% accuracy on 500-record labelled sample; used LDA topic modelling to surface top 10 complaint/praise themes. Build Power BI dashboard tracking daily sentiment score, volume spikes, and competitor comparison for real-time brand health monitoring.
Retail Sales Forecasting & Insight Engin
June 1, 2026 – Present
Cleaned 50,000+ rows of 3-year retail transactional data; built a Facebook Prophet time-series model achieving MAPE of 6.8% for monthly revenue forecasting. Designed Power BI executive dashboard with 8 KPIs (revenue trend, top SKUs, regional heatmap, YoY growth), reducing manual reporting by ~70%. Identified top 3 underperforming product categories via cohort analysis - insights translated to a 12% simulated revenue uplift in scenario modelling.
Data Analytics Job Simulation
Deloitte
June 1, 2026 – Present
Data Visualisation: Empowering Business with Effective Insights
Tata Group
June 1, 2026 – Present
Python Programming Internship
IIT BHU, Varanasi
June 1, 2026 – Present
O-Level Certification
NIELIT
June 1, 2026 – Present
Cyber Security: From Beginner to Expert
Udemy
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a breadth of application areas within data science, from HR/placement management to retail sales and social media analytics. This diversity suggests adaptability and a willingness to tackle different problem domains. The certifications and research paper presentations indicate a proactive learning attitude and engagement with the broader technical community, which aligns well with a culture of continuous improvement and knowledge sharing. The target role of Data Science is well-aligned with the skills and projects presented.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a results-oriented approach, focusing on quantifiable impacts (e.g., reducing unauthorized data exposure by ~30%, reducing manual reporting by ~70%). The academic achievements, including presenting research papers and participating in conferences, suggest initiative and a drive for continuous learning. However, without direct work experience, it's difficult to assess operational fit in a professional team setting or stress handling capabilities.