I don't just manage
crypto products
I trade them too
100,000+ app downloads. 5+ years in the markets. ACCA student. I build crypto products from the inside as someone who actually uses them every day.
0
App downloads led
5+ yrs
Active crypto trading
0
Live tools built
ACCA
Pursuing
Crypto Product Lead
Active Crypto Trader
ACCA Student
Prop Firm Trader
Narrative & Macro Research
DeFi · Web3 · Spot · Futures
React · Python · API Integration
👋 Who are you? Jump straight to what matters most to you
Scroll down and read everything, it's all here.
Featured Case Study
How I shaped Chart AI's product direction ⏱ 3 min read
⭐ Featured Project
Crypto Product Lead
● Live on Play Store
Chart AI, Crypto Charting & Analysis App
⚠ The Problem
Retail crypto traders lacked a mobile-first charting tool combining real-time technical analysis, automated pattern recognition, and actionable market context in one place. Existing tools were desktop-heavy, expensive, or built by people who'd never traded a single candle.
✓ My Approach
As the sole in-house crypto domain expert, I bridged trader needs and engineering output, identifying underserved features, scoping them with trader-first thinking, coordinating development, and validating every release from a practitioner's lens.
0
Total Downloads
#1
Domain Expert on Team
11
Months Leading Product
Multi
Roadmaps Owned
Specific contributions
- Automated Pattern Recognition · I scoped the logic, set the accuracy benchmarks, and validated every output against my own live trades · now the feature traders open the app for daily
- Home Screen UX Overhaul · I directed the UI redesign around how a trader actually moves through the app · cut the path to a live signal from 3 taps to 1
- AI Market Analysis Tools · I defined the logic and validated outputs against live markets before sign-off · shipped 3 live intelligence tools (narrative, news, macro)
- Feature Prioritization Gate · I stress-tested every request against my own trading sessions first · killed low-value features before dev and kept sprints lean
- Crypto Content & ASO · I led keyword targeting and trader-first positioning · sharpened messaging to the actual trader ICP
Key Product Decisions
Why automated analysis over more chart types?
After analyzing trader behavior, users spent more time seeking entry signals than exploring chart layouts. Automated pattern recognition delivers repeated daily value, chart type variety is a one-time choice. Signal generation keeps users coming back.
How did I validate before committing dev resources?
I stress-tested every proposed feature against my own trading sessions first. If I couldn't see myself using it while a trade is live, it didn't make the roadmap. This eliminated speculative features and kept the sprint lean.
What was the hardest product tradeoff?
Balancing simplicity for retail vs depth for experienced traders. Solved with progressive disclosure, clean defaults with advanced layers accessible but not mandatory, keeping both cohorts engaged.
"Never invest in a business you cannot understand."
— Warren Buffett. The same holds for building one: I trade the markets my products serve, so every feature is judged from understanding, not assumption.
Lessons Learned
Mobile-first means tap-first
Domain expertise is a product moat
Ship fast, learn fast, compound
Retention > Acquisition for trading apps
Speed of feedback matters as much as accuracy
Internship, iTechGemini
3 months · 2023
Crypto product research, feature analysis, and content development. Learned the full crypto product workflow from ideation through delivery and stakeholder communication.
Technical Background
React · Python · Full-stack
I evaluate feasibility honestly, estimate effort accurately, and communicate with engineers in their language, eliminating the translation layer that slows most PMs down.
Proof of Work
Evidence, not claims ⏱ 2 min per tab
How I actually think and work, documented.
PRD: Automated Pattern Detection Engine
Overview
ProblemTraders miss chart patterns due to screen fatigue and multi-timeframe complexity
GoalAutomate recognition of 12 high-probability chart patterns across 3 timeframes
Success Metric≥70% accuracy vs manual ID; 20%+ DAU increase within 30 days of launch
PriorityP0, Core feature for Q1 roadmap HIGH
User Pain Points (from trading experience)
- Scanning 20+ charts manually takes 2–3 hours, patterns missed by the time user acts
- Most pattern tools use lagging indicators, signals arrive after the move
- No mobile-native solution exists, existing tools are desktop-only
- False positives erode trust faster than missed signals
Feature Scope
In ScopeHead & Shoulders, Double Top/Bottom, Bull/Bear Flags, Triangles, Wedges, Cup & Handle
Out of ScopeElliott Wave (complexity vs accuracy tradeoff), Harmonic patterns (v3 candidate)
Timeframes1H, 4H, 1D, highest signal-to-noise ratio based on years of hands-on trading
Acceptance Criteria
- Pattern overlay renders within 800ms of symbol load MUST
- Confidence score displayed (Low / Medium / High) with color coding MUST
- Push notification on new pattern detection (opt-in) SHOULD
- Historical hit rate visible per pattern type NICE
Domain Rationale
- 1H/4H/1D chosen over lower TFs, retail traders are trend-followers, not scalpers
- Confidence score prevents over-reliance, trading is probabilistic, not deterministic
- Excluded harmonic patterns, too subjective for automated detection at current accuracy
🔍
Competitor Analysis
Market Gap: Crypto Charting Apps
Analyzed 8 top crypto charting apps on App Store and Play Store. Consistent gaps: no mobile-native automated analysis, no narrative context, UX designed for desktop traders forced onto mobile.
Key insight: Every major player treats mobile as a "viewer", we treated it as a primary trading surface. That's the positioning gap.
👥
User Research
Retail Trader Pain Points
Synthesized user feedback, competitor app store reviews, and personal trading experience to identify top 5 recurring pain points: signal overload, pattern fatigue, slow loads, missing macro context, poor alert systems.
Most apps solve charting. We solved decision-making. That's a different product entirely.
| Feature | Chart AI (Us) | TradingView Mobile | Coinigy | Delta App |
|---|---|---|---|---|
| Automated Pattern Detection | ✓ Yes | ✗ No | ✗ No | ✗ No |
| Mobile-First UX | ✓ Native | ~ Adapted | ✗ Poor | ✓ Yes |
| Narrative / Macro Context | ✓ Built-in | ✗ No | ✗ No | ✗ No |
| AI Analysis Layer | ✓ Yes | ~ Premium only | ✗ No | ✗ No |
| Free Tier Value | ✓ High | ~ Limited | ✗ Paid gate | ✓ Good |
I directed UX decisions based on how traders actually behave in markets, not how designers assume they do.
Before, Original Dashboard
Flat menu with 12+ items on home screen
All indicators shown by default (clutter)
Chart loaded after 3 taps
Alert system buried in settings
No macro or news context on chart view
After, My UX Direction
Focused home: watchlist + top signal
Indicators hidden by default, toggled on demand
Chart opens from one tap on any symbol
Alert icon always visible on chart view
News + macro widget inline with chart
Before, Pattern Alerts
No pattern detection existed
Users had to scan charts manually
No confidence scoring system
After, My Product Spec
12 patterns auto-detected across timeframes
Push notification on new pattern formation
Confidence score: Low / Medium / High
How I connect macro, narrative, and technical signals, the same mental models that shape every product decision.
Narrative Research
Identifying crypto narratives before they peak
Narrative cycles follow: early adopters → influencer amplification → retail FOMO → peak → rotation. I track social velocity, developer activity, and liquidity flows to identify narratives at stage 1–2.
"Be fearful when others are greedy, and greedy when others are fearful."— Warren Buffett
Macro Analysis
DXY, liquidity cycles & crypto correlation
Crypto doesn't trade in isolation. A weakening DXY with expanding global liquidity (M2) is historically the most reliable macro tailwind for BTC. Built Crypto Macro Intelligence because no mobile product connected these dots for retail traders.
"Gold is money. Everything else is credit."— J.P. Morgan
Technical Framework
Why I prioritize 4H/1D over lower timeframes
Lower timeframes generate noise. 4H and daily structures capture institutional order flow, the only flow that moves markets meaningfully. This informed every pattern detection feature I specced: designed around timeframes that matter.
"The big money is not in the buying and the selling, but in the waiting."— Jesse Livermore
Products Built
Tools I built because they didn't exist
Each started as a trading problem I couldn't solve with existing products.
Live
Know what the market is chasing before the crowd does
An AI-powered crypto sentiment & narrative intelligence tool built entirely on free public data. Every 10 minutes it collects hundreds of headlines from RSS, Google News, Reddit, CoinGecko, and derivatives data, scores sentiment with an ensemble of VADER, CryptoBERT, and a trained meta-model, and turns it into a single 0–100 sentiment index, bullish, bearish, or neutral, with a daily email brief.
- 0–100 sentiment index, relative to 30-day baseline
- Bloomberg-style live terminal: news feed, narratives, heatmap, forecast
- Honest scorecard tracking real hit-rate vs BTC price moves
- Personalized daily email brief per subscriber
PythonFastAPICryptoBERTDocker
🔗 Join waitlist →Roadmap: Public launch, Stripe paid tiers
Live
Read the market's macro backdrop in real time
One explainable 0–100 score for the global macro regime — dollar, rates, inflation, growth and central-bank policy — updated 24/7 and validated against history. The context professional desks have, built for retail.
- Live macro regime score (0–100) with confidence levels
- Signal-contribution weighting + live indicator z-scores
- AI-generated analysis & full score timeline history
- Email alerts on regime flips and score-level crossings
- Central-bank stance tracker + US economic calendar
PythonFRED APIReactCharts
🔗 Open live tool →Live · free email alerts
Live
Manual edge, systematized
Algorithmic trading system built on years of manual experience. Proven discretionary setups encoded into rules-based, emotion-free execution.
- Rules-based entry, exit & position sizing
- Backtested across 2020–2025 market cycles
- Max drawdown & daily loss limit built in
- Paper trading phase before live deployment
PythonBacktestingExchange APIPandas
🔗 View demo →📊 BacktestingTarget: Live Q3 2026
Impact
Measurable results
📈
5+
Years Active Trading
Crypto, US Equities, Prop Firm
🛠
0
Live Tools Built
Narrative, News, Macro Intelligence
📜
ACCA
Student
Currently pursuing qualification
🔍
Solo
Crypto Domain Expert
Only trader on the product team
⚡
Multi
Market Cycles Lived
Bull, bear, DeFi, NFT, L2, AI narratives
🏦
1yr
Funded Prop Trading
Professional risk management applied
About
Why I build crypto products
My philosophy
Why crypto?
I've been in these markets long enough to know most crypto tools are built by engineers who've never traded, or traders who can't build. That gap is where I live. I understand both worlds and translate between them to build products that actually work in the markets.
What makes me different?
I test every feature I spec in live market conditions before committing dev resources. My trading account is my most honest product validation tool. If I wouldn't use it while a trade is live, it doesn't ship.
What am I building toward?
A world where retail crypto traders have the same quality of tools as institutional desks, at a price they can afford. I'm building products that close the information asymmetry between retail and institutional, one tool at a time.
The combination that's rare
₿
Crypto Trader (5+ years)
Spot, futures, DeFi, lived through every major cycle
🎯
Product Lead at iTechGemini
Joined Chart AI and led UI, features and product growth
📜
ACCA Student · In Progress
Financial rigor anchors every product decision
💻
Technical Background
React, Python, I can build what I spec
🏦
Prop Firm Experience
Professional risk management discipline
Background
Education & Career Journey
How I got here
2021 – Present
Active Crypto Trader
Started trading crypto, spot, then futures, then DeFi. Survived the 2022 bear market. Traded through NFT, L2, and AI narrative cycles.
2025
Internship at iTechGemini
Crypto product research, feature analysis, content development. First time applying trading knowledge to a product context.
2025 – Present
Crypto Product Lead at iTechGemini
Joined Chart AI to lead UI, features, and product direction as sole crypto domain expert on the team.
2025 – Present
Prop Firm Trading
Funded account trading with professional risk rules. Max drawdown limits, position sizing discipline, no emotional decisions.
2025 – Present
ACCA
Pursuing the ACCA qualification to anchor every product decision in financial rigor, valuation, and risk discipline.
Next goal
CFA Program
After completing ACCA, adding CFA to combine professional financial rigor with crypto market expertise.
Qualifications
📜
ACCA
Association of Chartered Certified Accountants
⏳ Currently pursuing
📊
CFA Level 1
Chartered Financial Analyst
📅 Planned 2026, after ACCA
₿
Crypto Trading
Spot · Futures · DeFi · Prop Firm
✓ Active since 2019
🏢
Crypto Product Lead
iTechGemini · 2025 – Present
✓ Sole crypto domain expert
💻
Technical Skills
React · Python · REST APIs · Data Analysis
✓ Self-taught builder
Skills & Stack
What I bring to the table
🎯 Product
₿ Crypto & Trading
💻 Technical
📜 Finance & Credentials
📜
ACCA
Association of Chartered Certified Accountants
⏳ In Progress
Want to build something together?
Open to crypto product roles, trading tool collaboration, fintech opportunities, and research partnerships, remote or Karachi-based.
🎯 Ideal Role
Crypto Product Lead / Manager at a crypto startup, exchange, or fintech
📍 Location
Remote globally or on-site in Karachi, PK
⚡ What I bring
Domain expertise, trading credibility, execution speed, financial rigor
🤝 Open to
Full-time roles, consulting, product advisory, research collaboration
Usually responds within 24 hours