I'm Daniel LeBlanc. Data/Strategy-Guy with a passion for building things from the ground up ...who also enjoys hiking, woodworking, and spicy food. I, like many people with a career in Data, stumbled into this world.
I studied Finance at UGA , because I enjoyed learning about the markets and how unpredictable they are. Financial Mathematics, Derivatives, Algorithmic Portfolio Theories were some of my favorites.
This led me into my first job as a Data Analyst for JPMorgan. There, I analyzed everything under the sun about the 16,000+ devices in Chase's ATM fleet. Besides descriptive analytics & reporting, I predicted ATM errors before they happened, and advised senior execs on how to allocate a $120M budget to replace ATMs.
I also learned that my passion was for DATA and I would spend nights and weekends learning how to code and finding ways to apply what I learned on the job.
For the next move in my career, I required a role that exercised critical thinking and technical skills. I thought a career in management consulting would be fascinating and mentally stimulating, but I knew that in a typical generalist role data often takes a backseat. Similarly, I thought to work as a quant for a market maker or hedge fund, but I didn't want to work vigorously behind a desk only working with numbers...
Luckily, I found a team at McKinsey that struck a good balance with what I was looking for: consulting with a heavy slant towards advanced analytics. At the Firm I consulted & advised several of the top retail banks in North America on their omni-channel strategies and contact center operations. I also co-led McKinsey's industry-wide Contact Center Benchmarking Study and built the first banking industry-wide call-level database. On top of it, we would run experiments, causal ML models, and provide novel insights about consumer behavior never seen before. This was ultimately pitched and sold across the banking industry as an add-on to the Benchmarking Study.
I enjoyed building this "product" and developing ML models so much, I decided that this should be my job.
Since then, I've been a part of several startups, working as a Data Scientist, a Data & Machine Learning Lead, and Head of Engineering amongst others. I've loved the thrill of joining an early-stage project, and seeing ideas come alive! I've worked on the most high-level initiatives (e.g. building a tech roadmap, defining an MVP), developed and fine-tuned the low-level features (e.g. automate deployment processes, create computer vision models, migrate data pipelines/architectures), and gained some perspective along the way (e.g. fostering a collaborative and productive team, avoiding common startup pitfalls, communicating with others(!)).
If you've read this far, you must be willing to know what I'm up to now, right?
I'm looking for new challenges with innovative teams that have a shared interest in shaking things up, building something new and exciting, and having fun along the way. I love working with data, and I especially love helping others to navigate it, no matter where they are in their "Data Journey".
Whether you're:
just starting and you need help with solution discovery, data strategy, or roadmapping;
building your data "irrigation system" to get our applications really humming;
or you need to build an AI thingamajig, fast (!)
...I would love to help! Just reach out and let's chat!
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