Meet Arturo Fernandez: a Staff Data Scientist who’s as comfortable building churn models as he is tending to the office plants. He plays a key role in helping Attentive better understand our customers while embodying the curious, collaborative spirit that drives our data team forward.

On the Attentive Data Science team, no two days look exactly the same—but that’s part of what makes the work exciting. From collaborating with cross-functional partners to experimenting with cutting-edge AI tools, my role combines problem-solving, creativity, and teamwork. I get to partner with brilliant colleagues across Engineering, Product, and Go-to-Market teams, all while driving impact for our customers. 

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Here's a look at a recent day in my life

7:30am - Wake up!

I answer six math questions to turn my alarm off (tell me you’re a Data Scientist without telling me you’re a Data Scientist), followed by two follow-up alarms. What can I say, I fall prey to the snooze button!

8:30am - Head to the office

I take the train every morning to get to the office. That means a lovely morning exchange with fellow New Yorkers at Union Square station. 

9am - Office rituals

My first action items are water and coffee. We have a Bevi machine for water and an espresso machine. I take my time making myself an iced mocha. I kick off a latte drink on the machine, fill up a cup with ice, grab the Ghirardelli chocolate powder, mix it into the finished hot latte, pour that into the iced cup, and we're good to go. 

As the office Plant Dad, on my way to my desk, I take a cursory look at the snake plants to see how they're doing. I have a small forest of plants in my apartment, so I like to keep an eye on the ones at the office. It's always a treat to see new, sustained, and healthy growth. When I need a quick break from work, I tend to go around and check in on the plants as well. 

9:10am - Start the day

I kick things off by looking over the pull request (a proposed change to our production code through our version control system, GitHub) from yesterday. After running some final checks, I review Slack for any urgent updates across my DMs and team channels.

10am - Deploy churn model production code & kick off Metaflow jobs. 

A big part of my role is building models that help the business better understand our customers’ behavior and retention. Everything on the churn model looks good, so I deploy it to production and begin to launch Metaflow backfill jobs. Simply put, that means the model is now set to run automatically and learn from all the historical data we feed it—kind of like giving it the full story before it starts making predictions. To generate a historical record, we have to run it a number of times as if it were running in the past (e.g., each month for this past year). I keep a close eye as the jobs run, monitoring progress and double-checking that the outputs look right.

11am - Experiment with Claude Code

With our deployments humming along, I set up Claude Code, a tool that our AI Developer Experience team recently rolled out company-wide. They did an impressive job piloting it, and now I get to be one of the early adopters. Setting it up involves troubleshooting and familiarizing myself with the user experience so I can use it to improve my workflow.

11:30am - Collaborate with Business Intelligence (BI) Engineering

Next up: I connect with our BI Engineering partners to talk through orders, revenue, and conversions data and pipelines. These discussions help us connect the dots between historical context, the current state, and future applications—like how we align customer success with business objectives through smarter attribution windows.

12pm - Lunch

I grab lunch with my Data Science  teammates and catch up after some recent PTO. We talk about family, travel, and a bit of shop talk—it’s a great reminder that Attentive isn’t just about the work. The people here really make the culture what it is.

We have an amazing menu of lunch options at our offices, facilitated by Parkday. We order individual meals in advance from local restaurants. I'm hard-pressed to pick a favorite, but I usually pair my lunch with our hibiscus tea or lemonade on tap—if I really feel like going wild, I grab an orange soda from the kitchen.

Today, I ordered the Fried Chicken Box with collard greens from Pies ‘n’ Thighs. It was between that and the Fried Chicken Box with Mac ‘N’ Cheese. I went for the healthier option.

12:45pm - Prepping for meetings

Before the afternoon meeting block, I pull notes, dashboards, and documents together. Laying out agendas and expected outcomes helps me keep conversations focused and productive.   

1:30pm - Cross-functional sync

I join a meeting with partners from RevOps and the Revenue Org to review the status of churn modeling and revenue forecasting projects. We align on priorities for the rest of the quarter and start to frame what Q4—our busy season, thanks to Black Friday Cyber Monday—might look like. 

2pm - Development 1:1 with my manager

At Attentive, managers meet with their direct reports at least bi-weekly to align on existing projects, build trust, and have growth conversations. Today, we have a wide range of topics on the agenda, from career advancement and personal development to strategy, prioritization, and developing even stronger cross-functional partnerships.

2:30pm - Focus time

I check on my production jobs, and good news—they’re running great! I go through my usual checklist to understand health and performance:

• The standard output and error logs look good. 
• The model output to MLFlow and Snowflake look good. 
• The Argo Workflows and Metaflow Web User Interfaces (UIs) show expected, normal behavior. 

Then I take a deeper dive into Claude Code. I use it to create a claude.md file, make some small file changes, experiment with asking to interact with the GitHub Command-Line Interface (CLI), and ask it to ingest and review some of my existing project codebases.

The churn model needs one last routine to aggregate multiple accounts associated with a primary user, so I ask Claude to incorporate a function I wrote in my prototype Hex Notebook into the existing project codebase.

You have to be very specific with Claude to get the best outcomes. In summary, I ask it to update the flow, utilities, and SQL files accordingly. It does a decent job getting 80% of the way there with a small layer of modifications needed to match the practices I've established. Ultimately, I end up having to do a deep dive on a Pandas warning. With a bit of tinkering and documentation reading, we have a working solution for production now.

These experiments are the fun part of the job: testing, iterating, and learning. We're very lucky that Attentive promotes an always-learning mindset through our team culture, learning stipend, technical book clubs, lunch and learns, and other growth opportunities.

4pm - Go-to-Market partnership on AI strategy

I meet with a member of our Sales team to chat about AI strategy—everything from churn modeling to relationship scoring to vendor evaluation. Recently, Attentive was named Yotpo’s preferred SMS and email partner, which is an exciting moment for us!

These conversations are energizing because they show how data Science directly supports our go-to-market success.

4:30pm - Wrapping up the day 

Before logging off, I prepare a pull request and run a quick revenue analysis ahead of a meeting I have tomorrow.

Looking at the data, it’s clear we’re in an exciting moment: as we've matured into a multi-channel company, our revenue streams have diversified and we’re tackling competitive challenges head-on. Initiatives that kicked off in late 2024 and the first half of 2025 are bearing positive signals as we continue to innovate and enhance our industry-leading marketing platform for our customers.

It’s motivating to know that the work I do helps our customers—and our company—thrive in this landscape.

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Conclusion

As I log off for the day, I’m struck by how much variety and impact this role brings. I get to learn, experiment, and collaborate with brilliant teammates who are passionate about solving big problems. That blend of curiosity, teamwork, and business impact is what makes Attentive such a unique place to grow as a data scientist—and why I’m excited to see what tomorrow brings. Want in? We’re hiring!