Okay so, you're probably wondering what makes me different. Well, for starters, it's just me. I don't have a sales team, or layers of project managers. When you work with me, you're working directly with the person doing the work. This means no miscommunications, no inflated invoices, and a direct line to someone who understands the tech and your business needs.
I know Seattle's a hub for tech, but a lot of small to medium businesses still feel like advanced data projects are outta reach. My goal is to bridge that gap, making real-world machine learning and data science accessible without the usual overhead or corporate jargon.
## What I actually do for Seattle clients
Most of my projects for Seattle-based companies fall into a few buckets: either building a specific predictive model, setting up some data automation, or helping you figure out if a machine learning idea even makes sense to pursue. Think things like predicting customer churn, optimizing inventory levels based on past sales data, or automating data cleanup processes that are currently a huge time sink. I'm not here to just talk about AI; I'm here to build it and make it work for your business.
I often start with a small, focused pilot project. This lets us test the waters, prove the value of a machine learning approach, and get a tangible result in a relatively short timeframe. It’s a low-risk way to see how data science can move the needle for your business here in Washington.
## How a Seattle engagement usually goes
1. **Initial Chat (1-2 days):** We hop on a quick 20-minute call. You tell me what problem you're trying to solve, and I'll ask some questions about your data and what you're hoping to achieve. No hard sell, just figuring out if there's a good fit. 2. **Deep Dive & Proposal (1 week):** If it sounds like I can help, we'll schedule a longer, more detailed discussion, usually 60-90 minutes. I'll dig into your existing data, systems, and processes. Based on that, I'll send over a fixed-fee proposal outlining the scope, deliverables, and timeline, usually within a week of our deep dive. 3. **Project Execution (4-12 weeks):** Once we agree on the proposal, I get to work. This phase involves data cleaning, model building, testing, and integrating the solution (if applicable). I'll provide regular updates, usually weekly, so you always know where things stand. For most practical machine learning models, this phase typically runs between four and twelve weeks. 4. **Handover & Support (Ongoing):** After the project is delivered, I'll provide documentation and training so you and your team can confidently use what I've built. I'm also available for ongoing support or further enhancements, should you need them down the line. It's important to me that what I build for your Seattle business actually lasts and is usable.
## What it costs, roughly
I work on a fixed-fee basis for most projects. This means you know the exact cost upfront, with no surprises. It also helps us both stay focused on the defined deliverables. While I can't give exact numbers without knowing your project, typical engagements often start in the mid-four figures and go up from there, depending on complexity and duration. I aim to provide real value without the eye-watering prices of larger consulting firms.
## Who I'm usually NOT a fit for
I'm probably not the right fit if you're looking for someone to manage a team of 20 data scientists, or if you need someone to just talk about 'AI strategy' for months without actually building anything. I also don't do highly regulated, public-facing applications where a single error could cause catastrophic loss of life or property. My sweet spot is practical, data-driven problem-solving for small to medium-sized businesses in places like Seattle who need to get things done.
## Getting in touch
If you're in Seattle, Washington, and have a data problem you think machine learning or data science could solve, let's chat. The quickest way to figure out if I can help is to book a 20-min call. You can find my calendar link on the contact page.
FAQs — Seattle
How do I know if AI is worth it for my Seattle business?
The best way to figure this out is to identify a specific, measurable business problem you're trying to solve. If you have data related to that problem, chances are machine learning could offer a solution or at least shed some light on it. We can discuss this on a quick call.
Do you work with companies outside Seattle?
Yes, absolutely. While I make an effort to connect with local businesses in specific cities like Seattle, my services are available remotely to companies across the United States. Location isn't a barrier to getting good data science help.
What does the first 2 weeks look like?
The first two weeks usually involve our initial discussions to understand your problem, followed by me preparing a detailed, fixed-fee proposal. If we proceed, the first actual project work would begin shortly after that agreement, focusing on data collection and initial exploration.
I don't have a lot of data. Can you still help?
It depends on the specific project. While machine learning generally thrives on data, sometimes we can start with smaller datasets or work on strategies to help you begin collecting the right data. It's definitely something we'd explore early on to see what's feasible.
What kind of ongoing support do you offer after a project is finished?
Once a project is complete, I provide comprehensive documentation and am available for continued support on an as-needed basis. We can discuss retainer options for longer-term maintenance or new feature development if that's something your Seattle business requires.