What does an AI engineer and tracking expert help with?

An AI engineer and tracking expert helps businesses build production AI workflows while also implementing analytics, event tracking, and attribution systems so performance can be measured accurately end to end.

Do you set up GA4 and Google Tag Manager?

Yes. Services include GA4 architecture, Google Tag Manager web and server-side tagging, event taxonomy design, conversion API integrations, and QA for reliable reporting.

Can you improve marketing attribution and conversion tracking quality?

Yes. Typical work includes fixing broken event pipelines, standardizing UTM governance, improving match quality, reducing data loss, and building attribution-ready data models.

Do you build dashboards for founders and marketing teams?

Yes. Dashboards are built for executive reporting and operational decisions using tools such as Looker Studio, Power BI, Tableau, Metabase, and custom SQL-backed reporting layers.

Can you support both AI product development and analytics implementation in one engagement?

Yes. Combined engagements are common when teams need AI features, event instrumentation, user analytics, and business reporting delivered as one measurable system.

AI Engineering, Data Analytics, and Conversion Tracking

Build AI products and measurement systems that prove growth.

I design and implement production-ready AI workflows, analytics pipelines, and tracking architectures for businesses that need accurate attribution, reliable reporting, and scalable automation. I specialize in GA4, Google Tag Manager, server-side tracking, dashboard engineering, and AI-driven product features.

Start a Project View Case Studies

99% Tracking QA coverage target
48h Audit turnaround for most websites
3x Faster decisions with clean dashboards

GA4 GTM Web + Server BigQuery Attribution LLM Apps SQL Dashboards Tracking QA Automation

Attribution Coverage

92.6%

Cross-channel touchpoints mapped

Conversion Quality Trend

+27.4%

Improved event integrity after GTM and server-side rebuild

Data + AI Workflow

1 Event Tracking (Web/App)
2 QA + Validation Layer
3 Warehouse + Modeling
4 LLM / Predictive Automation
5 Dashboard + Alerts

Event Stream QA

Live

purchase schema valid
lead_submit ID stitched
page_view UTM missing
signup_start sent to GA4 + BigQuery

Services

AI engineering and analytics services built for measurable outcomes

I combine AI implementation, data analytics engineering, and tracking expertise so your business can launch smarter features and trust the numbers behind growth decisions.

AI Product Engineering

Design and build AI-powered workflows, assistants, classifiers, retrieval systems, and internal tooling with production-quality APIs, guardrails, and observability.

LLM feature integration
Prompt + workflow orchestration
API and backend implementation

Analytics Engineering

Build clean data layers for reporting and decision-making with event schemas, SQL transformations, warehouse models, and dashboard-ready metrics definitions.

Event taxonomy design
SQL modeling and data pipelines
KPI layer standardization

Tracking & Tag Management

Implement and repair web/app tracking using GTM, GA4, dataLayer standards, consent-aware tags, and server-side tagging to improve data quality and resilience.

GA4 + GTM implementation
Server-side tagging setup
Tracking QA and documentation

Attribution & Measurement Strategy

Improve channel measurement confidence with attribution-ready schemas, UTM governance, conversion mapping, and data consistency checks across ad platforms.

Attribution troubleshooting
Channel conversion mapping
Measurement plans

Dashboards & Reporting Systems

Create fast, decision-first dashboards for founders, marketers, and ops teams with drill-down views, anomaly monitoring, and stakeholder-ready reporting outputs.

Executive dashboards
Marketing performance reporting
Automated alerts and QA views

Data QA, Governance & Privacy

Reduce tracking errors and reporting disputes with naming standards, validation rules, PII safeguards, consent mode alignment, and maintenance documentation.

Tracking audits
Data quality checks
Privacy-aware implementation

Work

Representative project snapshots for AI, analytics, and tracking

These examples are structured to be SEO-friendly and portfolio-ready. Replace company names and metrics with your real results before publishing to maximize trust and conversion.

B2B SaaS / Revenue Analytics

Rebuilt attribution and lead tracking for a multi-channel SaaS funnel

Implemented GA4, GTM, CRM event mapping, and SQL reporting models to eliminate duplicate leads, standardize funnel stages, and improve marketing attribution confidence.

62%reduction in unattributed conversions

28%lower cost per qualified lead after tracking fixes

1 sourceof truth dashboard for marketing + sales

Designed event taxonomy and naming standards across landing pages and product signup flow
Created GTM container governance and conversion validation checklist
Built executive and channel-level dashboards with agreed KPI definitions

Ecommerce / Server-Side Tracking

Improved conversion signal quality with server-side tagging and event QA

Migrated fragile client-side tags to a server-side measurement architecture, improved event match quality, and added validation alerts for checkout and purchase events.

+19%measured conversions captured after migration

9.1/10average event quality score in QA checks

35%faster debugging time for tracking incidents

Implemented GTM server-side tagging and privacy-aware routing patterns
Standardized ecommerce events for ad platforms and analytics reporting
Added QA dashboards to monitor drop-offs, missing IDs, and schema drift

Operations / AI Workflow Automation

Built an AI-assisted analytics workflow to classify requests and surface insights

Delivered an AI pipeline that summarizes operational inputs, tags high-priority items, and syncs structured outputs to dashboards for leadership visibility.

47%faster triage on recurring operational requests

3xmore insights reviewed per weekly ops meeting

24/7automated categorization and alerting coverage

Built API-based AI workflow with audit-friendly logging and retries
Mapped outputs into analytics tables and dashboard-ready schemas
Added monitoring for prompt regressions and classification quality

Stack & Workflow

Technical depth across AI, analytics engineering, and tracking implementation

The strongest outcomes happen when AI systems and measurement infrastructure are designed together. I build both the product logic and the analytics layer needed to evaluate impact.

AI & Backend

Python, FastAPI, Node.js, OpenAI APIs, Retrieval Workflows, Vector Stores, Docker, REST APIs

Analytics & Tracking

GA4, Google Tag Manager, GTM Server-Side, dataLayer Architecture, Conversion APIs, Segment, Mixpanel, Amplitude

Data & BI

SQL, BigQuery, PostgreSQL, dbt, Looker Studio, Power BI, Tableau, Metabase, KPI Modeling

Measurement Operations

Tracking QA, Event Validation, UTM Governance, Attribution Mapping, Reporting SLAs, Documentation

How I run delivery

01

Audit & Goals

Review current tracking, reports, and AI/automation opportunities. Define business goals, conversion events, and reporting audiences.
02

Architecture

Design event taxonomy, tagging strategy, data flows, schemas, dashboards, and AI workflow components with implementation priorities.
03

Implementation

Build tags, APIs, dashboards, automations, and validation checks. Ship iteratively with clear release notes and QA checkpoints.
04

Optimization

Track accuracy, speed, and business impact. Refine schemas, improve tracking reliability, and expand AI use cases after baseline stability.

Ideal for: startups, ecommerce brands, SaaS teams, agencies, and operators who need both technical execution and measurement clarity.

About

A portfolio focused on systems that perform and data you can trust

I work at the intersection of AI engineering and data analytics implementation. That means I do more than ship features: I also make sure the tracking, dashboards, and attribution logic are accurate enough to guide decisions.

Teams usually hire me when they have one of these problems: analytics numbers do not match, conversion tracking is incomplete, dashboards are too slow, AI ideas are stuck in prototypes, or no one owns the measurement architecture. I solve those gaps with practical implementation and documentation that your team can actually maintain.

If you need an AI engineer, analytics consultant, GA4 / GTM expert, or tracking specialist who can connect product, marketing, and data workflows, this site is designed to make that easy to evaluate.

Common Engagement Types

Tracking audits and GA4/GTM rebuilds
Server-side tagging migrations
Attribution and funnel measurement fixes
AI workflow implementation and analytics integration
Executive dashboard and KPI system setup

What Clients Get

Clear implementation scope and milestones
Documentation for handoff and team adoption
QA checks for tracking reliability
Metrics definitions aligned with business goals
Practical recommendations, not generic decks

SEO Keywords Covered Naturally

AI engineer portfolio, data analytics consultant, conversion tracking expert, GA4 implementation, GTM specialist, server-side tracking, attribution modeling, dashboard developer, analytics engineer, tracking QA.

Availability

Open to freelance consulting, project-based implementation, and long-term technical partnerships. Remote-friendly and available across time zones.

Discuss your project

FAQ

Frequently asked questions about AI engineering, analytics, and tracking projects

These FAQs are written to support user trust and search visibility while answering common hiring questions.

What kind of businesses do you work with?

I work with startups, ecommerce brands, SaaS companies, agencies, and operators that need stronger analytics, more reliable conversion tracking, or AI-powered workflows connected to measurable outcomes.

Can you fix a broken GA4 or GTM setup without rebuilding everything?

Yes. Many engagements start with an audit and targeted repairs. If the current setup is salvageable, I document what to keep, what to deprecate, and what to rebuild to improve data quality without unnecessary disruption.

Do you provide tracking plans and technical documentation?

Yes. Documentation is part of the deliverable. This usually includes event naming conventions, trigger logic, dataLayer specs, KPI definitions, QA checklists, and handoff notes for developers or marketers.

Can you connect AI features to analytics so we can measure usage and business impact?

Yes. I can instrument AI features with meaningful events, build reporting views for adoption and performance, and connect outputs to downstream dashboards so teams can evaluate what is working.

How fast can a project start?

Most projects can start with a short discovery call and audit. A tracking audit or analytics review is often the fastest first step because it reveals immediate fixes and defines the right implementation scope.

Do you work with existing teams and agencies?

Yes. I often collaborate with in-house developers, marketers, and agency partners to implement tracking, analytics, and AI systems without disrupting existing workflows.

Contact

Need an AI engineer and tracking expert for your next build?

Share your current setup, what is not working, and what you want to measure. I can help with AI implementation, GA4/GTM tracking, attribution fixes, dashboards, and analytics strategy.

Email

contact@shahzadmalik.com

linkedin.com/in/muhammad-shazhad

GitHub

github.com/Shahzadmalik47

Typical reply window: within 24 hours on business days.

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