Hi, I'mAnshul Kumar Singh
Data Analyst|SQL · Python · Power BI · Tableau
Proprietary trader turned data analyst — I turn real-time market data into P&L, risk, and business insight. Now bringing that instinct to SQL, Python, Power BI, and Tableau.
Tools I work with
Every session on the trading desk is a live exercise in reading data under pressure. I'm channeling that instinct into a data analytics career.
"Comfortable reading volatile, high-pressure data — now turning that instinct into business dashboards and decisions."
About Me
Turning Market Data into Business Insight
Proprietary trader managing funded accounts since 2024 — reading real-time market data, tracking P&L, and applying risk management under pressure. Alongside trading, I'm completing an MBA in Analytics & Data Science at Manipal University Jaipur, with hands-on training across SQL, Python, Power BI, and Tableau.
I'm actively seeking a full-time Data Analyst role where I can bring that same discipline to business data — risk, forecasting, and performance dashboards.
Experience
Where I've Worked
Skills
Where I Stand Today
Data Analysis & Visualization
SQL, Python (Pandas, NumPy), Power BI, and Tableau.
PROFICIENTStatistical & Quantitative Analysis
Hypothesis testing and statistical reasoning in Python and R.
PROFICIENTRisk & P&L Management
Live strength from active prop trading — the core differentiator.
LIVE STRENGTHMarket Trend & Pattern Recognition
Reading live, volatile data under pressure on the desk.
LIVE STRENGTHPortfolio
Projects In Build
SQL
A beginner-to-intermediate SQL project: database setup, data cleaning, exploratory data analysis, and business-question queries — top customers, category-wise sales, monthly trends, and shift-based order patterns.
An intermediate SQL project modeling a library system — branches, employees, members, books, and issue/return tracking. Covers CRUD operations, CTAS, stored procedures, and advanced queries like overdue-fine calculation and branch performance reporting.
SQL analysis of Netflix's content catalog — content-type distribution, most common ratings, top countries by content volume, genre breakdown, top directors and actors, and keyword-based content categorization.
An end-to-end Python + SQL pipeline on Walmart sales data — cleaned and transformed with Pandas, loaded into MySQL and PostgreSQL via SQLAlchemy, then queried with complex SQL to surface revenue trends, top categories, and profit margins by branch.
Python
An end-to-end credit risk pipeline on the German Credit Dataset (1,000 customers) — EDA, categorical encoding, an Extra Trees classifier predicting loan default probability (~77% accuracy, ROC-AUC ~0.80), and a Streamlit app for real-time risk scoring.
A production-ready ML pipeline on 58,592 policyholder records predicting insurance claim likelihood — compared Decision Tree, Random Forest, and XGBoost (94% accuracy, 100% recall on claims), with a Streamlit app for instant underwriter risk scoring.
Power BI
A Power BI dashboard analyzing Facebook and Instagram ad campaigns — platform-specific views, core KPIs (impressions, reach, CTR, CPC, conversions), and demographic/engagement breakdowns to guide ad spend and targeting decisions.
A Power BI job simulation for PwC Switzerland — an executive dashboard tracking call centre KPIs (CSAT, resolution rate, abandonment rate, speed of answer), agent performance benchmarking, and call volume trends by hour and day.
Data Visualization
Completed a forensic-technology data analysis simulation — built a Tableau dashboard and used Excel to classify data and draw business conclusions.
Education
Academic Background
MBA — Analytics & Data Science
Manipal University Jaipur (MUJ)Bachelor's Degree, Physical Science
University of DelhiJob Simulations — Forage
Completed real-world Deloitte (data analytics & forensic technology) and PwC Switzerland (Power BI call-centre analytics) job simulations, both verified by Forage.
Credentials
Continuous Learning
IBM
2 Professional CertsGoogle AI
Professional CertMicrosoft
Business AnalystCoursera / Univ.
Michigan, UC Davis
11-course professional certificate — IBM, completed September 10, 2026. Covers data analytics fundamentals, Excel, SQL and relational databases, Python, data visualization with Cognos and Python, and a capstone project.
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12-course professional certificate — IBM, completed September 27, 2026. Covers data science methodology, Python and SQL, data visualization and analysis, machine learning models, generative AI, and a capstone project.
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3-course specialization — University of California, Davis, completed September 6, 2026. Covers SQL fundamentals, data wrangling, SQL analysis, A/B testing, and distributed computing with Apache Spark.
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5-course specialization — University of Michigan, completed July 9, 2026. Covers Python fundamentals, data structures, web data access, databases, and a capstone in data retrieval, processing, and visualization.
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6-course professional certificate — Microsoft, completed June 20, 2026. Covers business analysis fundamentals, data analysis in Excel, process modeling in Visio, requirements gathering, Power Platform, and project delivery.
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7-course professional certificate — Google, completed June 1, 2026. Covers AI fundamentals plus applying AI to brainstorming, research, writing, content creation, data analysis, and app building — including a portfolio of AI-built artifacts.
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Digital Credentials
Let's Work Together
Let's Talk
Data.
Actively seeking full-time Data Analyst opportunities — bringing real-world market experience, risk discipline, and a growing analytics toolkit to the table.
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