There is an opening for a principal data science position on my team at Gainwell. I was promoted to a director role a few months ago (I was an individual contributor for 4+ years), so this position will directly report to me.

There are of course mixed reviews if you google Gainwell Technologies what it is like to work there. Gainwell is a big organization (maybe over 6,000 employees at this point). Any big org it can be totally different if you work for a different team. So I can describe what it is like to work for me and on my team.

I have been at HMS (which then merged with Gainwell) since the end of 2019. The way I describe what Gainwell does, we administer Medicaid claims for many states, but most of what my team does is support efforts to fix bad Medicaid claims (more commonly referred to as Fraud/Waste/Abuse). Fix means for the most part the bill was wrong (too high or for the wrong services), or the bill should have gone to a different person (seems trivial, but billions are sent to Medicaid that should be sent to a commercial carrier or car insurance in the US per year).

I started as a data scientist, went up through a ranks with a promotion every few years (our levels are JR->Advisor->Principal->Sr Manager->Director). For a list of projects folks on my team are working on:

• structured labeling for medical records to help with audits
• supervised machine learning models to help make prior authorizations go faster
• structured extraction for many types of documents to auto-verify the contents
• improving supervised machine learning models in production to improve identification of third parties liable for claims
• building tools to auto-identify potential Fraud/Waste/Abuse in large databases of claims
• making our master name index record linkage project run much faster and have more matches

This specific role will be to help with the last bullet. So it is a mix of the more recent fad of GenAI tools, but also we do a bunch of traditional machine learning as well. This role I want folks to know at least two {SQL,Machine Learning,Python}.

We are mostly just solution architects, using python to glue together different processes to make smart decisions across the org. Gainwell is a very federated and older company built up from acquisitions over the years – my team is one of the few that works across the org with many different teams. While many people at Gainwell have a data science title, my team is the AIML (artificial intelligence and machine learning) team at Gainwell.

This work is important, just my team is associated with models that help save states 9 figures on Medicaid claims per year (I imagine it is well over 10 figures across the whole org). For a bit more about the team:

• all remote, we have a mix across the continental US. Most of Gainwell is in central, so often the schedule follows central time for meetings (think many stand-ups at 9:30-10am eastern)
• my team has a bunch of smaller groups working on individual projects (think 2 or 3 max assigned to work on these projects). This position will be number 8 under me.
• We are always tied to revenue when we take on a project (think generally if we cannot justify at minimum 1e6 in savings or increased revenue, we will not take on that project). This is important, as we are not just treated like IT filling tickets, we are deeply integrated with the business teams we are delivering solutions for.
• You do not have to make sales, we are building things internally (think your clients are different teams inside of Gainwell). We have more work than we can do.
• We are committed to building things fast. Those first 4 bullets are things we built in the past 6 months and are already generating millions of dollars of revenue.

So we are working with legacy on-premises Hadoop systems, or Databricks, or AWS deployments calling Bedrock or openai, or traditional machine learning – we just get a new project and figure it out. Do not take this as you need to know everything (if you put some random tech on your resume like Docker or time series analysis, be prepared to answer a random question about it when I interview you!) But I do want smart folks who can learn and adapt to the situation at hand. Really the only consistent tech across projects is python and SQL.

For work life balance:

• I have worked on the weekend a total of 2 times in my tenure at Gainwell that I can remember (and those were less than 1 hour)
• Because we are remote, we are uber flexible with scheduling (need to drop off or pick up your kid from school during the day, can very likely work around that schedule). Basically all I care about is you get your work done, and individual contributors will just need to figure out a few regular meetings (like stand ups or other meetings with the business group you are working with)
• Flex PTO (basically only need permission if you are taking more than a week off)

I shared this on LinkedIn and I slightly dread it (I will get a million messages) – but readers of this blog are different. If you think you may be interested in private sector, feel free to reach out. (Lets just get criminologists to take over, Gio now also has his own team at Gainwell.)

Since this is a principal position, recent grads will be tougher to advocate for, but I can give feedback what I am looking for (and it is good for you to be on my radar for future positions). If you are a superstar and the salary is not enough, reach out and we can have a one on one chat.

The main thing is most of my network uses R, and not python. Basically the way I view it is a weighted scale. If you are really good at R (have public code examples and packages), I can be more confident you can learn python. If you knew python, and just had the typical replication code sets in python (a much lower bar). No excuses to learn python, I wrote a book to help with that.

The differently LLM providers have released computer use tools, Google’s Gemini being one of the most recent ones. They way these work, it submits and image, and then does tasks given general instruction, actually manipulating the mouse and keyboard, asking for human in the loop input at various stages, etc. They seem cool but I am lacking clear examples where I would use them.

They really make sense for very complicated workflows that vary. The things that make the most sense to spend some time trying to automate though are boring things – things that have a specific set of inputs and outputs, and the machine can entirely make those route decisions based on rules you define at the onset. When I was a crime analyst, I worked with all sorts of janky and old desktop software that I would need to generate reports and email those results to key individuals for example.

Here as a day project, I created a set of python functions to record your keyboard and mouse inputs, and then replay those inputs. The python code is here, it ends up being pretty simple (mostly written by ChatGPT and slightly modified by me). And here is a YouTube video demonstration showing what you can do.

So even if you have software that does not have an easy way to integrate with other code, here you can just record your movements and replay them with python on a schedule to accomplish that monotonous task.