Jen Vetter’s Post

How to land a data science job and make it last. With COVID pandemic, recession and all, many data scientists have recently lost their jobs. Here are some tips to help reduce the anxiety of getting laid off. When looking for a new role: 👉 Ensure your machine learning efforts align with the company's revenue stream for long-term job security. 👉 Your role is more secure when directly connected to the core revenue-generating activities of the company. After all, their main objective is profit. On the role: 👉 Become irreplaceable by acquiring a broad skill set, such as data engineering and frontend/backend engineering. Finally, don’t be (too) frustrated if it doesn’t turn out the way you dreamed it. Layoffs can provide clarity on life priorities. After all, a job isn't probably as rewarding as family time and pursuing personal dreams. And there’ll surely be more opportunities down the line! Based on the podcast from AI Stories: https://buff.ly/3RDz5Lu

I had to make >800 applications and sit through 65 interviews before landing my first job. Sounds insane but that was my reality when I graduated in the US - during a recession! The job market was brutal, and every door seemed to be slammed shut—especially in the tech and VC industry, where I desperately wanted to work. And unfortunately, I wasn’t from Harvard, Yale or Stanford or any other Ivy League. I watched as others walked into jobs I knew I was capable of doing, and honestly, it drove me nuts. Every application, email, and interview hit a dead end. But quitting was never on the table although I was dead-broke and finding it hard to make ends meet. So, when Y2K came around and COBOL became a hot skill, I rolled up my sleeves & taught myself basic mainframe coding. Eventually, landed an entry-level job as a COBOL programmer with Keane – I hated every minute of it 😥 Fortunately, just before I completely lost my mind, I got a call from MicroStrategy in Boston and was quickly hired as a pre-sales consultant. But I knew the real action was in their Washington D.C. HQ. So, I took a shot in the dark and wrote directly to Michael Saylor the founder & CEO, asking for a role in their new venture Strategy.com I got the role 😅 > Moved to D.C. > 2 years later, I was Director of Strategic Partnerships at a company that was the toast of Wall Street and darling of the tech world💪🏼 We went from a $100m to $40b mkt cap in that time. Yeah, let that sink in🚀 That job & my time in the US shaped me into who I am today🙏 But here’s the thing - this struggle wasn't just about landing a job- it was also about proving to myself that I was as good as the best. To every struggler out there, the road is tough, but every "no" gets us closer to a yes, and that one "yes" has the power to change everything in our lives ✅ So, keep pushing, keep learning, and keep fighting for what you deserve coz our breakthroughs are out there. Sometimes they just need a little time to find us 🤗

Data Driven decision making is a key trend across all industries but particularly a focus for the HR and TA community right now according to a recent TALiNT Partners event I attended. At Instant Impact, we've prioritised transforming our data function from reporting to analytics so that we can offer our clients truly dynamic, real time data visualisation - and it's self serve. We are only at the start of our transformation but this is a pretty big step - and brought to life so well by our very own Data Lead Lee Welsh, grab a coffee it's well worth the watch! #datadriven #transformation

I'm so over the endless buzzword treadmill. 🙄 With all the tech layoffs in the past year, I didn’t hear anyone talking about right-sizing or streamlining to achieve synergy. But now we're trying to build up our decision intelligence to support prescriptive analytics using architectures like data mesh and data fabric. Our digital automation processes will enhance our business intelligence by integrating emotional intelligence. Maybe using these buzzwords will catch a recruiter's eye, but it won't make you better at your job. Instead of chasing the latest jargon, focus on developing actual skills and delivering results. That's what sets you apart in the long run. 💪 What buzzwords do you find most overused in your industry? Share in the comments! For the recruiters: #DecisionIntelligence #PrescriptiveAnalytics #DataMesh #DataFabric #DigitalAutomation #EmotionalIntelligenceBI For everyone else: #ProfessionalDevelopment #SkillBuilding Happy Memorial Day weekend, everyone! 🇺🇸☀️

New Opportunity

Big news: april is #2 on Will Reed’s Top 100 Culture List. At april, AI isn’t just a tool – it’s at the core of our culture. By embracing experimentation and data-driven decisions, we’re able to build, iterate, and ship smarter tax solutions faster than ever. That’s how we’re on track to become the first new national e-file provider in 15 years. Innovation like this doesn’t happen without a culture built on curiosity, relentless improvement, and a forward-thinking mindset. Oh, and we’re hiring. Check the comments 👇 for open roles and the full list! #willreedstop100 #gigalert #fintechjobs

Amidst economic uncertainties and job security concerns, one thing remains clear - the demand for skilled technology professionals is on the rise. With 26% of tech recruiters increasing their recruiting budgets, the tech industry continues to show resilience and growth. At Kforce, we understand the importance of staying ahead in this dynamic landscape. Partner with us to navigate the ever-evolving tech market with confidence.

This senior software engineer broke free from a mediocre life. Ten years at the same company, dreaming of a bigger paycheck—but it wasn’t just about the money. The toxic culture was draining him. He knew he deserved more but didn’t know how to break out of the cycle. It started with taking action on his own terms. He reached out to me. We started with a resume makeover, and suddenly, FAANG recruiters were reaching out. Then came the grind: LeetCode marathons System design deep dives Crafting stories that truly captured his impact He put in the work through mock interviews, pushing past the doubts that had held him back. Seven weeks later? 💥 A 133% salary increase at NetApp. He didn’t settle. He didn’t wait. He took charge of his own narrative and turned his career around. The lesson? You don’t have to stay stuck, tolerate toxic environments, or keep settling for less. You just need the right guidance and the guts to go for it. Don't wait another 10 years. Your dream job is out there. Break free from mediocrity.

The recent massive layoffs of big tech companies teaches us 2 important things: 1. Build broader skills: The layoffs have shown that relying solely on a narrow set of skills can be risky. For example, many finance professionals in tech companies focus solely on financial modeling and reporting for their specific product or division. When the company had to make large-scale cuts, these specialists found their skills were not easily transferable to other areas of the business. It's important to have a diverse range of skills that can be combined to create unique solutions that others cannot easily replicate. In finance, this could mean having expertise not just in accounting and analysis, but also in areas like data visualization, business process improvement, and strategic planning. 2. Network with people outside your company Your professional network is a valuable asset, so it's important to nurture it. Attending industry events outside your immediate field can help you connect with new people and open up new opportunities. For finance professionals, this could mean going to conferences or meetups focused on topics like financial technology, sustainable investing, or corporate governance - areas that may be adjacent but not directly part of your day-to-day work. Building these external relationships can provide you with new perspectives, potential job opportunities, and insights that can be applied back to your core finance role. Be prepared for anything that comes your way in your career.

I've been waiting for someone to write up an analysis on this, but I haven't seen it yet, so here it goes: AI is heavily contributing to the tech layoffs. Github Copilot claims to make engineers 55% more efficient. But measuring developer productivity is a notoriously hard problem. Every CEO is asking him/herself "Am I getting 55% more efficient workers, or are my employees working 55% less without a drop in output?" One sure way to find out - fire 55% of your engineers and see if you start missing release dates. I think the winners coming out of this will be the companies that adopt modern engineer productivity measurement tools, reorg to smaller teams with more responsibility, and cut a smaller fraction of their engineers. They will ACCELERATE - while the 55% layoff-ers will see short-term boosts in financials.