I help entry-level, non-technical professionals get their first data analyst role | Data Analyst @RBC | Data Career Coach

I help immigrants and career-switchers land analyst roles—without burning out on certificates.

By day I build decision-grade analytics (currently at Autodesk). By night I run Data Career Compass, where we treat your job search like a product launch:
Market → Positioning → Portfolio → Distribution → Interviews.

My POV:
Most candidates try to add more tools. Winners learn to package their value. Your portfolio isn’t a gallery; it’s a sales page for your judgment.

Receipts:

→ Professionals land interviews by aligning projects to business outcomes (not toy datasets).

→ My frameworks have been used across finance, tech, and education to translate experience into results.

→ Built data products and controls in regulated environments (RBC Capital Markets) that leaders rely on daily.


What you’ll get here:

→ Weekly breakdowns of real projects (SQL, Python, dbt, DuckDB, Looker/Tableau/Power BI).

→ Storytelling patterns that turn insights into action.

→ Templates that remove friction: portfolio briefs, stakeholder one-pagers, interview scorecards.

Coming April:

I’m launching a coaching program designed for mid-level and senior professionals ready to transition into analytics.

This isn’t an entry-level bootcamp—it’s a career accelerator that helps you reposition your existing experience, communicate business value, and step confidently into data-driven roles.

Work with me:

↳ Cohorts + 1:1 coaching → DM “HIRED”

↳ January program for mid/senior professionals → DM “APRIL” for early access

↳ Guest workshops for teams and communities → DM “WORKSHOP”


I build analysts who think like product managers and communicate like consultants.

Peter Ndiforchu

Every data analyst has lived through this meeting.

Dashboard says: $1.2M
Finance says: $1.1M

Meeting topic for the next 45 minutes:

“Where did the $100K go?”

First theory:
Maybe a filtering issue.

Second theory:
Currency conversion.

Third theory:
Time zone mismatch.

Fourth theory:
Someone forgot to refresh the data.

Meanwhile the analyst is quietly thinking:

“Please don’t be a duplicated join. Please don’t be a duplicated join. Please don’t be a duplicated join.”

45 minutes later…

Root cause:

Someone exported the numbers to Excel
…and manually deleted a row “that looked wrong.”

New meeting scheduled:

“Aligning reporting methodology across teams.”

Welcome to data analytics.

Where 90% of the job is not finding insights…

It’s explaining why two numbers that should match… don’t.

If you’ve ever spent an hour chasing a mysterious variance in a meeting, you’re officially part of the club. 📊😅

Helping Non-Technical Professionals Build Data-Driven Careers That Travel Globally | Data Career Strategist | Senior Data Analyst @ Autodesk

Thom Ives, Ph.D.

Lead Data Scientist

Unify Consultants

Creating an AI bot to do frequent and specialized queries for Amazon.

Senior AI Consultant

Integrated AI Applications

Building a REST API hosted in Vercel that integrates with Stripe for payments. Tech stack is NextJS with Typescript using app router, Shadcn UI, Tailwind CSS, with Python and Jest testing.

Founder

Phoenix Intelligence

Founding member and technical advisor as Phoenix Intelligence helps clients use technology to achieve or exceed their goals.

Technical Advisor

Echo Global Logistics

* Developed two complete AI Web Apps, to be Outlook Add-Ins, to automate replies to quote request emails. They both used LLMs with Auto-RAG to perform entity identification. Front-end components, and FastAPI based back-end components all run from Docker containers. Did the same for the Front “Outlook Manager” app.
* Developed and delivered many models and helped the data science team to learn and use FastAPI and Streamlit served through Docker containers and Outlook Add-In Web Apps served via Apache.
* Developed a carrier manifest optimizer that saves ~10+% in carrier costs.

Senior Data Scientist

AI Strategy Corporation

. Worked on an AI architecture to rapidly process unstructured technical data sheets
. Programmed a fast document match math machine that grew real time
. Created tokenizers to rapidly find property elements in PDFs
. Developed a heterogeneous clustering algorithm to rapidly group property elements
. Built a text terms aligner that uses two lookup engines and a trained GloVe model
. Created a system of Python to SQL routines that generated the AI’s memory
. Built several Py-Selenium based dynamic web scrapers
. Started a data science community to share learning and mentor others in data science
. Gave many presentations to the UL community to spread data science appreciation

Integrated Machine Learning & AI

. Worldwide Mentoring grown from LinkedIn followers
. Writing an ML book with Packt and taught a course on the same
. Weekly “Integrated Mentoring” sessions - recordings on YouTube
. Technical and mentoring blog posts that address the data science community’s needs
. Bi-weekly tech chats where I help data scientists with detailed technical questions
. Frequently asked to keynote speak and present on data science topics

ON Semiconductor

. Used data science and python to automate testing of imaging die on wafers.
. Used software version control, testing, tuning, and benchmarking
. Mentored new engineers on how to automate their work with Python
. Developed a machine learning algorithm to automatically find image defects
. Updated, maintained, troubleshot test algorithms, applied them to new products

Algorithm Development Engineer

Hewlett Packard Enterprise

. Recipient of 25+ US Patents for many different types of devices
. Color Imaging: Created python based data science tools to adjust halftones across different printers / scanners. Ran psychometrics. Mentored and assisted 3 PhD graduate students in data science methods to accurately predict toner usage.
. Laser Cartridges: Developed statistical machine learning models for cartridge wear, automated data collection on laser cartridges in test to more rapidly ID problems; guided graduate students in modeling of toner dynamics for design improvements, served on their committees, and tested new cartridge designs.
. R&D of Micro-Electro-Mechanical Systems (MEMS): Coded simulations of mechanics, electrostatic motors and sensors, charged particle optical focused-emitters, and thermal performance using FEM, BEM, and lumped parameter modeling techniques for MEMS R&D. Specified and designed parts for, updated parts for, and constructed an R&D vacuum test system for performing laser-doppler-vibrometer dynamics studies using LabView coding for imaging and vision capture systems for MEMS testing; Used python to coordinate several computers to reduce cycle time in finding optimal solutions; Coded physical model simulations with python to control 3D surface animations to better characterize MEMS performance and quickly identify design problems.
. Leadership in Training: Originated site wide technical training to preserve knowledge through online videos.
. Parts Design: Faster more robust design & manufacture of plastic and sheet metal parts using design methodology and FEA.
. Disk Arrays: Continuing product engineer troubleshooting large storage disk arrays (RAID systems) and mechanical engineer.

R&D Engineer

University of Idaho

Assistant Faculty Member

Analyzing data to make predictions describes my 30+ year career. 

I love data science, machine learning, artificial intelligence, and multi-physics engineering, and can do a wide range of predictive analytics. 

Among my wide range of work, I have a particular passion around automating the flow and analysis of data and data visualizations including animation when necessary. It's not always about making predictions. It's also about giving actionable insights to the organizations that I serve.

My main language for the past 22+ years has been python, and I am skilled with many of pythons' modules. 

Other languages from my history of coding have been C, C++, FORTRAN, Basic, ACSL, MatLab Simulink, Labview, and AWK.

In August 2018, I started Integrated Machine Learning & AI providing services and instruction in the data science community.

In July of 2019, I joined AI-Strategy as their lead data scientist.

I also have wide business acumen. I am a successful and experienced real estate investor and was a licensed Realtor to support my real estate investing and more. I’ve worked in insurance and securities and was a certified life underwriter and held series 6 and 63 securities licenses. 

In summary, I’m an addicted data scientist and dynamic multi-physics systems modeler and analyst that loves to work with great people to improve the performance of business or products through better analytics, processes, and design.

I'd love to talk about DS, ML, AI, and engineering with you and your team,
Thom Ives

https://thomives.github.io/ThomIves/
https://integratedmlai.com​ ​ 
https://github.com/ThomIves

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