Okay so, let's cut to the chase. You're here because you've heard about machine learning, data science, maybe AI in general, and you're wondering if any of it can actually help your business. You're probably thinking, 'Is this just for big tech companies, or can my Lubbock operation actually use this stuff?' My goal with this page isn't to sell you a dream, it's to tell you what I actually do, how I do it, and if I might be a good fit for what you're trying to achieve. I'm not here to tell you I'm gonna change the world; I'm here to solve specific problems with data.
## What I actually do for Lubbock clients
When I say machine learning and data science, I'm talking about taking your existing data and using it to make better predictions or automate decisions. For a Lubbock client, that might mean building a system that predicts which of their customers are most likely to churn in the next quarter, so they can proactively reach out. Or maybe it's optimizing inventory levels by analyzing sales data and external factors like local events or weather patterns. I focus on concrete outcomes, not just fancy algorithms.
Another common type of project involves automating tasks that are currently manual and data-heavy. Think about processing invoices, categorizing customer feedback, or even just sifting through large datasets to find anomalies. If there's a repetitive, rules-based task that involves information, there's a good chance we can build a model to do it faster and more consistently than a human can, freeing up your team for more important work.
## How a Lubbock engagement usually goes
I like to keep things pretty straightforward. Here's how a typical project unfolds:
1. **Initial Chat & Discovery (1-2 Weeks):** We start with a free 20-minute call, then if it feels like a fit, we'll dive a bit deeper. I'll ask a lot of questions about your business, your data, and what problem you're trying to solve. This phase is all about understanding if machine learning is even the right tool for the job. I'll put together a short proposal outlining the problem, the proposed solution, and estimated timelines.
2. **Data Deep Dive & Preparation (3-5 Weeks):** Once we agree on a plan, I'll need access to your data. This is often the trickiest part; getting data clean and in a usable format takes time. I’ll work closely with your team to understand your databases, spreadsheets, and any other data sources. This is where the actual 'data science' often begins.
3. **Model Building & Prototyping (4-8 Weeks):** With the data ready, I'll start building the actual machine learning models. I'll keep you in the loop with regular updates, showing you early prototypes and explaining what the model is doing. We’ll test it against historical data to see how well it performs.
4. **Deployment & Handoff (2-4 Weeks):** Once we have a model that works, I'll help you get it integrated into your existing systems. This could be anything from providing you with a simple prediction file to helping deploy a more automated solution. My goal is for you to be able to use the solution independently, or with minimal ongoing support from me.
## What it costs, roughly
I know budget is always a concern. I generally work on a project-by-project fixed-fee basis after the initial discovery phase, so you know exactly what you're getting into. For smaller, focused projects, think in the ballpark of a few thousand dollars, stretching up to the mid-five figures for more complex, longer-term engagements. It really depends on the scope, the complexity of your data, and what kind of outcome we're chasing. I don't do hourly billing for projects after the discovery, it's just simpler for everyone.
## Who I'm usually NOT a fit for
I pride myself on being upfront. I'm probably not the right fit if:
* **You don't have any data.** Machine learning needs data to learn. If you're starting from scratch with no historical records, we might need to talk about data collection first. * **You're looking for a massive, multi-year staffing augmentation.** I'm a solo operator. I can handle specific projects and provide expertise, but I can't staff an entire data science department for you. * **You need something built yesterday.** While I work efficiently, these projects take time. If you have an unrealistic deadline or expect immediate, miraculous results, I'm probably not your guy. * **You're just curious about 'AI' but don't have a specific business problem.** I work best when there's a clear challenge we're trying to overcome with data, not just a general exploration of technology.
## Getting in touch
If any of this sounds like it might align with what your Lubbock business needs, I'd genuinely like to hear from you. The easiest way to figure out if I can help is to just have a quick conversation. No high-pressure sales, just an honest talk about your challenges and if machine learning or data science is even a viable path. Go ahead and book a 20-min call right here on my site. I look forward to hearing from you!
FAQs — Lubbock
How do I know if machine learning is worth it for my Lubbock business?
The best way to figure this out is to think about repetitive tasks or decisions you make that rely on data. If there's a clear problem you want to solve, like predicting sales or optimizing operations, it's likely a good candidate for machine learning.
Do you work with companies outside Lubbock, Texas?
Yes, absolutely. While I make an effort to acknowledge my clients' local areas, I operate remotely from Florida and work with businesses all over the United States. Location isn't a barrier to collaboration.
What does the first 2 weeks of an engagement look like?
After our initial chat, the first couple of weeks are usually focused on getting to know your business in more detail, understanding your data landscape, and refining the exact problem we're trying to solve. I'll often put together a mini-proposal or discovery report during this time.
What kind of data do I need to have for you to help?
You typically need historical data related to the problem you want to solve. This could be sales records, customer interaction logs, sensor data, or anything else that’s been collected over time. The more data, and the cleaner it is, the better.
Do I need to be a tech expert to work with you?
Not at all. My job is to translate complex technical concepts into plain language that makes sense for your business. You bring your business knowledge, and I'll bring the data science expertise. We'll work together.