Ms

Turning complex data
into

👋 Hi, I'm Mohib Siddiqui, a Data, BI & AI analyst building dashboards, pipelines and stories that help businesses understand the why behind the numbers.
Get in Touch Open Resume
MS
Master of Science
IT Management
★
Scholar with Distinction
Academic honors
Profile

The person behind the dashboards.

Mohib A. Siddiqui

I left Oslo and moved to the US to start over from scratch. New country, new culture, no shortcuts. I chose data because of the impact it has on real business decisions. A single insight or the right model can shift how an entire organization thinks and acts, and that is what keeps me in this field.

What excites me most right now is the intersection of AI and data. Not as a buzzword, but as a practical way to remove bottlenecks, speed up how teams move from raw information to decisions, and unlock clarity that simply was not possible a few years ago. I recently graduated with a Master of Science in Information Technology and Management from UT Dallas, and I am just getting started.

Based in
Dallas, TX · Oslo, NO
From
Oslo, Norway
Languages
English · Norwegian · Urdu
Education
MSITM, UT Dallas
Stack

What I build with.

Data Analytics & BI

Tools I use to analyze data, build dashboards, create reporting workflows, and translate business questions into actionable insights.

Primary Stack
Power BIDAXPower QueryPython / Pandas
Additional Tools
TableauQlik SenseMicrosoft ExcelPivotTablesVLOOKUPAzure Logic AppsAzure Power Automate
Work

Things I've shipped.

A mix of internship, academic and personal work across data analytics, BI and AI.

AI · AutomationIn progress

AI Support Automation

State-aware AI platform that classifies, validates, routes and resolves customer support requests through intelligent workflows. Combines Azure Logic Apps, an LLM model, Azure Functions and Azure Table Storage with seamless human escalation. Currently wired to Zendesk, but the architecture is tool-agnostic and can plug into any modern support platform.

Outcomes
  • 58% auto-resolution rate
  • 100+ tickets processed
  • <$0.01 infra cost / ticket
  • Designed for 30–50% support cost reduction at scale
Skills used
AI & Automation95%
Cloud & Tooling (Azure)90%
Azure Functions80%
API Integrations80%
Sports AnalyticsCapstone

NBA Schedule & Travel Impact — OKC Thunder

Python analytics pipeline studying how NBA scheduling factors affected the Oklahoma City Thunder from 2014–2024. Combined schedules, arena geospatial data, travel distance, rest and team stats to model back-to-backs and rest imbalance.

Outcomes
  • 10 seasons of schedule + performance data
  • Identified 26 OKC four-in-six stretches
  • Rest/travel burden ~3.8σ above league avg
  • Engineered Off/Def/Net Rating + TO Ratio
Skills used
Python (pandas, NumPy)90%
scikit-learn / modelling75%
Data Analytics & BI80%
Geospatial / Temporal analysis70%
View on GitHub
BCG X · Data ScienceCapstone

PowerCo Customer Churn Prediction

Built a churn analytics project for PowerCo, a fictional energy provider. Used EDA, feature engineering and ML to test whether price sensitivity drove churn — then translated findings into a non-technical executive deck.

Outcomes
  • ML models built + evaluated for churn risk
  • Customer, pricing & consumption features engineered
  • Found churn drivers go beyond price alone
  • Delivered exec-ready storytelling deck
Skills used
Python / scikit-learn85%
Feature engineering80%
Data Analytics & BI75%
Business storytelling90%
View on GitHub

More work

BCG · GenAI

AI-Powered Financial Chatbot

Rule-based AI chatbot delivering financial insights from 10-K and 10-Q reports, built during BCG's GenAI Junior Data Scientist Experience.

PythonNLP
BI · Power BI

Retail Sales Insights Dashboard

Interactive Power BI dashboard on 12,000+ rows of retail sales — analyzing trends, category performance, discount impact and KPIs via dynamic filters and DAX.

Power BIDAX
Data Engineering

Hotel Management Database System

Normalized PostgreSQL system for hotel operations — ER modelling, 3NF, DDL/DML, triggers, views, joins and aggregations across reservations, rooms and payments.

SQLPgAdmin
Analytics · KNIME

Customer Transaction Analysis Workflow

Modular KNIME workflow to preprocess, filter, aggregate and visualize customer transaction data — uncovering purchasing behavior and segmentation insights.

KNIMEData Analytics
Product · AI

Frugal.AI — AI Personal Finance App

End-to-end product concept + pitch deck for an AI personal finance app — vision, market sizing, personas, AI features, monetization and go-to-market.

Product StrategyAI Concepting
Strategy · IoT

Trace360 — Smart Asset Tracking

GTM strategy and pitch deck for an RFID + IoT asset tracking solution across food and pharma supply chains — pricing, distribution, IP and launch planning.

Market ResearchGTM Strategy
Journey

Where I've been.

Business Analyst Intern

Beats by Dre
Jun 2025 – Aug 2025
Remote · New York, NY
10K+ reviews analyzed 87% NLP accuracy +25% YoY sentiment
  • Analyzed 10,000+ Gen Z consumer reviews in audio tech (Python · pandas · NumPy), identifying 5 product features driving 70% of positive sentiment.
  • Built an NLP sentiment pipeline reaching 87% classification accuracy, uncovering a 25% YoY rise in positive sentiment toward wireless & noise-cancelling features.
  • Cleaned and structured raw text from multiple sources, cutting data noise by 35% and lifting downstream model input quality.
  • Shipped 3 interactive dashboards letting stakeholders spot emerging product opportunities 2× faster.

Data Analyst Intern

GameStack
Jan 2025 – May 2025
Remote · US
+22% availability +15% retention -10% delivery time
  • Analyzed rental & subscription data in Excel (PivotTables, VLOOKUP, Conditional Formatting), improving game availability by 22% and cutting idle inventory.
  • Ran pricing strategy analysis with What-If modelling + Power BI, contributing to a 15% lift in customer retention via optimized tiered plans.
  • Built dynamic Power BI / Power Query dashboards to monitor real-time delivery KPIs, driving a 10% reduction in delivery turnaround.
  • Modeled event usage patterns to optimize console allocation, cutting customer wait times by 25% during high-traffic periods.

Business Intelligence Intern

Norbygata Engros AS
Jun 2024 – Aug 2024
On-site · Oslo, Norway
+30% forecast accuracy -18% overstock +22% category profit
  • Built a dynamic inventory forecasting model integrating historical sales + promo calendars, raising stock prediction accuracy by 30%.
  • Analyzed seasonal sales & inventory trends, driving a 30% reduction in overstock and measurable food-waste cuts across key categories.
  • Used SQL on POS data (PC Kasse) to sharpen sales forecasting, improving inventory planning accuracy by 40%.
  • Led SKU-level performance reviews with cross-functional teams, lifting category-level profitability by 22%.
Studies

What I've studied.

2024 – 2026

MS, Information Technology & Management

The University of Texas at Dallas
Graduate Certificate in Business Analytics & Data Mining
2021 – 2024

BSc, Information Technology — Digital Economics & Leadership

University of Oslo
Focus on digital strategy, data analytics and product development
Get in Touch

Let's build something insightful.

Send me a message
+1 945 358 1108US
+47 972 91 981NOR