Building Career Expertise

Corporate jobs are dying. You just don't want to admit it yet. But the portfolio career is rising - and if you execute strategically, it delivers freedom with sustainable income. I've discussed how being a generalist within your organization makes you invaluable - connecting dots across teams and strategy. But this is fundamentally different. I'm talking about building a portfolio career independent of any single employer - based on your specialized expertise, proven outcomes, and professional brand. The future isn't traditional employment. It's ownership of your career architecture. From my experience in executive search working with elite leaders: those who've built genuine career security - with freedom, flexibility, and multiple income streams - all specialized early and narrowly. Nobody compensates generalists for high-trust, high-value work. You must be recognized for delivering one specific outcome. Master that, and everything else becomes scalable. Five portfolio career models: - Digital Products - Scalable courses, frameworks, templates (high upfront investment, significant long-term leverage) - Sprint Work - Two-week fixed-scope projects with defined deliverables (immediate revenue, repeatable) - Advisory Roles - Low time commitment, high strategic value (compensated for expertise, not hours) - Consulting - Deliver tangible outcomes, transition from projects to retainers - Fractional Roles - Part-time embedded leadership within organizations Critical principle: Establish recognition for one specific outcome. Then construct your service offerings around that expertise. Strategically combine models - perhaps one advisory retainer, one sprint project, and one digital product. This creates recurring revenue and prevents the feast-or-famine cycle that destroys independent careers. You don't need job security from a single employer. You need career security from diversified expertise. Sign up to my newsletter for more corporate insights and truths here: https://vist.ly/4bm9c #portfoliocareer #careeradvice #careerstrategy #consulting #futureofwork #executiverecruiter #eliterecruiter #jobmarket2025 #careeradvancement #fractionalexecutive #entrepreneurship

If you’ve ever walked out of an interview replaying every answer, worrying if you were likable enough, polished enough, or impressive enough, let me tell you something: none of that matters. Interviews aren’t about charm or perfection they’re about demonstrating that you solve problems and create impact. I break down exactly how top candidates approach interviews strategically and how you can too! 1. Stop selling potential start showing solutions. Every role exists because something in the organization isn’t working, isn’t scaling, or could be improved. Your goal isn’t to convince them you deserve the job it’s to show that you already operate at the level of the role and can immediately move things forward. 2. Your resume isn’t your story. Reading your resume aloud is boring. To stand out, you need to share examples using the CAR framework: Context, Action, Result. Show how your experience maps to real problems the organization is facing. For example: "I noticed your team recently expanded into new categories, which often creates operational challenges. At my last company, I worked with cross-functional teams to streamline approvals, improving launch efficiency by 25%." This positions you as someone who thinks like a peer, not a hopeful applicant! 3. Questions aren’t small talk they’re your superpower. At the end of every interview, you have a chance to demonstrate strategic thinking. The right questions signal leadership and curiosity: What does success look like in the first six months for this role?   What are the biggest challenges this role needs to solve immediately?   How do you define top performance here, and how do promotion decisions get made? These questions show that you’re already thinking about impact, results, and growth, and they set you apart from every other candidate who just says, “No, you covered everything.” 4. Follow-up is more than etiquette. A thoughtful follow-up reinforces your value. Reference a topic you discussed and demonstrate your understanding: "I’ve been thinking about our conversation around onboarding and am excited by the opportunity to streamline that process." This reminds them that you’re a problem solver who already adds value. The truth is, most people treat interviews as auditions. But career growth isn’t about being liked it’s about demonstrating your impact, asserting your value, and choosing the organizations you want to work with.

🌍 Africa's Energy Moment Is Now—But Don't Miss What's Really Happening TotalEnergies Tilenga project starts producing 149,000 barrels per day next month. CNOOC International Kingfisher development adding another 27,000 bpd. Across Africa, $41 billion in upstream investment is flowing in. The headlines make it sound straightforward: more oil, more opportunities, more growth. But I've spent two decades in these emerging markets, and I can tell you—the real challenge isn't geology or economics. It's execution. I've seen brilliant projects falter because instrumentation wasn't installed correctly. I've watched first oil get delayed because commissioning teams didn't understand the local context, the supply chains, the political realities. The difference between a project that succeeds and one that stumbles often comes down to teams that have actually been on the ground before. Africa's energy moment is real. The operators winning aren't the ones with the biggest budgets—they're the ones with partners who've learned the hard way. That's where CIRA & CIRA Overseas comes in—decades of experience across African and Middle Eastern developments. If you're working on African energy projects, I'd love to hear what's keeping you up at night. What's your biggest operational challenge right now? #AfricaOilGas #EnergyProjects #FieldCommissioning #OperationalExcellence #IndustrialExpertise #EnergyTransition #GlobalProjects #EngineeringLife #Instrumentation

Society taught us to value time over expertise. But we’ve been measuring value all wrong. We’ve always been taught: → Count the hours, not the skill → Pay for the process, not the outcome → Fast usually means carelessly done I used to have a similar mindset before I got into business. That if something didn't take hours, it wasn't valuable. But when I actually started hiring people who were both good AND fast at their job, I realized how wrong I was. I once hired a developer who fixed a problem in 20 minutes that I'd been stuck on for 3 weeks. And those 20 minutes weren’t just 20 minutes. They were years of him: → Breaking things → Fixing them → Breaking them again …until he could spot the issue before I even finished explaining it. I wasn't paying for 20 minutes. I was paying for the 10 years it took him to solve my problem that fast. So next time you hire an expert: 1. Pay for the outcome, not the hours.  2. Ask about problems solved, not time taken. 3. Value the years of expertise, not the speed of delivery When someone solves your problem in 30 minutes, you're not paying for 30 minutes. You're paying for every hour they invested before you showed up. You owe them for those years, not the minutes. Found this valuable? Please reshare with your network! ♻️ And follow Noemi Kis✨ for daily growth tips!

You're in an AI/ML Engineer interview at OpenAI. Interviewer: "We want to fine-tune a large language model on domain-specific documents. How would you approach it while avoiding catastrophic forgetting?" You: "Fine-tuning requires a balance between learning the new domain and retaining general capabilities. I’d start with data preparation and sampling strategies." Interviewer: "Go on. What steps would you follow?" You: "Stepwise: 1. Dataset curation: Ensure the domain-specific corpus is clean, representative, and diverse. Include counterexamples to avoid overfitting. 2. Adaptive fine-tuning: Use techniques like LoRA or adapters rather than full-parameter tuning. Keeps base capabilities intact while learning new patterns efficiently. 3. Regularization strategies: Implement dropout, weight decay, and embedding regularization to prevent catastrophic forgetting. 4. Validation and evaluation: Track domain-specific metrics (accuracy, F1, ROUGE) alongside general LLM capabilities to ensure balance. 5. Iterative checkpoints: Save intermediate models and evaluate incremental improvements to detect drift or forgetting early. Interviewer: "How do you handle tokenization issues in a new domain?" You: "I’d analyze the token distribution. If domain-specific terms are frequently split, consider adding them to the tokenizer vocabulary. This reduces out-of-vocabulary embeddings and improves model performance. Interviewer: "Deployment concerns?" You: "I'd monitor latency and memory footprint. Use model distillation or quantization if needed. Maintain fallback to base model in production for queries outside the domain. Observability and versioning are critical for safe rollout." Interviewer: :) #AI #LLMs

I have interviewed over 300+ candidates in the last 10 years at Freshworks, Microsoft, and now at Atlassian. In this time, one pattern has become very clear to me. The engineers who grow fastest are not the ones who know the most tools. They are the ones whose fundamentals are rock solid. That is exactly what I look for in interviews. Let me explain with an example. Say, I ask a very simple question: A user hits a button on the UI, and some data gets stored. Walk me through what happens, end to end. You can talk about any stack you like.  React, Angular, Django, Spring, does not matter. From the answer, I usually see: 1. Candidates who only stay at the surface. The moment I ask, deeper questions like what actually happens on the network when that API call goes out? They look lost. They know the tool, but not the idea behind it. 2. Candidates with shaky basics. They can go very deep, but only inside their familiar stack. They explain every layer of their current service, every class and pattern. Then I change the context slightly. Imagine the same feature, but now your database is relational instead of NoSQL. Suddenly the answers are poor. Because their understanding sits on the surface of one framework, not on concepts like transactions, isolation, caching, complexity, consistency. 3. Candidates who go from first principles. These are the people I try hard to push for. They start from first principles. Browser collects input, serializes it into an HTTP request, DNS resolves the domain, the request hits a load balancer, goes to an app server, which validates, writes to storage, and returns a response. I ask about performance. They talk about: - where latency comes from  - why indexing helps, but also where it can hurt - what happens on a cache miss - how they would protect the database with rate limiting or backoff I ask about failure. They bring up: - timeouts and retries - idempotent operations - what should be logged and monitored Sometimes they do not know a tool I mention, and they are honest about it. For early-career engineers, this is very important. Your stack will change. Your company will change. The fundamentals stay with you everywhere. As an interviewer, I am not testing whether you have memorized the exact syntax of some library. I am testing whether, if I drop you into a new codebase with a new stack, you can build a mental model of the system, ask the right questions, and make good decisions. That comes from fundamentals. If you invest in those, every new framework, language, and job switch becomes easier. --- P.S: Say Hi on Twitter: https://lnkd.in/g9H82Q98 -- P.P.S: Feel free to reach out to me if want to chat about interview preparation or how to move to the next level in your career, happy to help here: https://lnkd.in/guttEuU7

At the just-concluded The Industry Discourse, I addressed over 200 people on a question many young professionals ask: How can I play a role in oil and gas without an oil and gas background? First, understand this: the industry, like any business, runs on a value chain. Broadly, we speak of the Upstream, Midstream, and Downstream. But within each, there are multiple layers of activity. Energy isn’t just about rigs, refineries, and equations. It is equally about finance, policy, communication, sustainability, law, human capital, and business strategy. Engineers may build the systems, but businesses also need people to manage them, finance them, regulate them, and tell their stories. Your discipline doesn’t exclude you—it positions you. At its core, every business exists for profit. The oil and gas sector has two objectives: 1. How to make profit. 2. How to do so sustainably—ensuring continuous, long-term value creation. So, how can you position yourself? 1. Build energy literacy — Even if you’re not an engineer, learn the basics of energy production, distribution, and consumption through free courses, industry reports, and workshops. 2. Find intersections — Identify where your field meets energy. For example, economists can analyze pricing, data analysts can model consumption, communicators can drive public engagement, and finance graduates can structure investments that fund new energy projects. 3. Network intentionally — Join platforms like the SPE, attend forums, and engage professionals on LinkedIn to learn the industry’s language and showcase your passion. 4. Start small, think big — Publish insights, research trends, or volunteer in sustainability projects. Small, consistent steps build a strong track record beyond your degree. Just to reiterate: your degree is not a death sentence. It is your responsibility to understand the industry you’re in, identify value points or problem areas, and show how your discipline can help drive solutions. SPE NIGERIA COUNCIL SPE Lagos Section 61 Society of Petroleum Engineers International

Want to join LSEG ? London Stock Exchange Group has been actively hiring for data science roles in the past 1–2 months. And over the last month, I had the opportunity to interview around 5 candidates, and one common pattern stood out. Many candidates had impressive resumes filled with technologies, frameworks, tools, and project experiences. However, when the discussion moved beyond definitions and into practical application, many struggled to explain what they had actually built, why certain decisions were made, or what challenges they faced. Knowledge is important. Learning concepts, completing courses, and understanding theory are all valuable. But simply listing a skill on your resume doesn't make it your skill. A resume is not a wishlist of technologies you want to learn someday. It is a reflection of what you can confidently discuss, demonstrate, and apply in real-world scenarios. I've seen candidates mention: • Machine Learning models they couldn't explain. • Cloud services they had never deployed on. • Frameworks they had never worked upon. • Projects they couldn't describe it at design and deployment level. The problem isn't a lack of knowledge. The problem is overrepresenting experience. My suggestion to job seekers: ✅ Only mention skills you can confidently answer questions about. ✅ Build at least one hands-on project for every major skill you add to your resume. ✅ Be ready to explain your design choices, challenges, and learnings. ✅ Focus on depth over breadth. Five well-understood skills are far more valuable than twenty buzzwords. ✅ Be honest about what you've learned versus what you've actually implemented. Interviewers are not looking for candidates who know everything. They are looking for candidates who can demonstrate genuine understanding, problem-solving ability, and a willingness to learn. A candidate who honestly says, "I've recently started learning this technology and built a small project around it," often leaves a better impression than someone claiming expertise without practical experience. In the long run, authenticity builds credibility. Credibility builds trust. And trust opens more doors than any keyword-stuffed resume ever will. Be honest. Be practical. Let your work speak louder than your resume. #CareerAdvice #Interviews #JobSearch #DataScience #MachineLearning #SoftwareEngineering #CareerGrowth #TechCareers #Hiring #ResumeTips #LondonStockExchangeGroup

*My final round of interview at Goldman Sachs* 𝘈𝘯 𝘪𝘯𝘤𝘪𝘥𝘦𝘯𝘵 𝘰𝘧 𝘸𝘩𝘺 𝘪𝘴 𝘪𝘵 𝘢𝘭𝘸𝘢𝘺𝘴 𝘳𝘦𝘤𝘰𝘮𝘮𝘦𝘯𝘥𝘦𝘥 𝘵𝘰 𝘸𝘳𝘪𝘵𝘦 𝘰𝘯𝘭𝘺 𝘸𝘩𝘢𝘵 𝘪𝘴 𝘵𝘳𝘶𝘦 𝘪𝘯 𝘺𝘰𝘶𝘳 𝘳𝘦𝘴𝘶𝘮𝘦?   During my Articleship, I had performed Journal Entry (JE) Testing, which I included in my resume.   The interview started with the usual questions but quickly honed in on my JE Testing experience: 1. What is JE Testing? 2. Why is it performed? 3. How do you conduct it? The questions delved deeper, into areas only someone with hands-on experience would understand: 4. How are JE routines decided? 5. If you audit a listed client for 20 quarters, and they become aware of the “specific words in narration routine,” how do you maintain audit effectiveness? 6. What is the element of unpredictability in JE Testing, and how do you incorporate it? 7. With a limited number of JE routines, how do you ensure unpredictability over 20 quarters? 25 minutes of the 35-minute interview focused on this single topic. I could navigate through it smoothly because I had truly performed JE Testing and knew its intricacies inside and out. Interestingly, a similar situation occurred in another company’s interview. This experience was a powerful reminder: 1. Be honest about your skills and experiences on your resume. 2. It can make all the difference, not just in passing an interview, but in demonstrating your genuine expertise and integrity. Have you ever had a similar experience where your actual knowledge saved the day? Share your stories below!

The US Power Market Has a Workforce Problem That Money Can't Solve. Everyone is focused on AI-driven load growth. Everyone is talking about generation. Everyone is talking about transmission. But what happens if there aren't enough people to build any of it? The reality is that billions of dollars are being committed to power infrastructure projects across the US, yet the industry faces an increasingly difficult challenge: Experienced talent is becoming a bigger bottleneck than capital. Utilities like Dominion Energy, Duke Energy Corporation, Southern Company, American Electric Power (AEP), NextEra, and Xcel Energy are all investing heavily in grid expansion, transmission upgrades, generation projects, and infrastructure to support unprecedented demand growth. At the same time, major contractors and EPCs such as Quanta Services, Inc., MYR Group, Burns & McDonnell, Black & Veatch, Kiewit, and Michels Corporation are competing for the same pool of experienced professionals needed to deliver these projects. The challenge? Utilities can secure funding. Developers can raise investment. Contractors can win projects. But finding experienced professionals who can lead substation builds, transmission programmes, grid modernisation initiatives, and large-scale capital projects is becoming increasingly difficult. Many of the industry's most experienced professionals are approaching retirement, while demand for talent continues to accelerate. This creates a fascinating dynamic: ⚡ The power market isn't just competing for megawatts. ⚡ It's competing for expertise. Over the next decade, I believe the organisations that win won't simply be those with the strongest balance sheets. They'll be the ones that can attract, develop, and retain the best people. Infrastructure gets built by people before it gets built by machines. And right now, experienced people may be the most valuable asset in the entire power sector. What are you seeing in your corner of the industry? Are talent shortages becoming a bigger risk to project delivery than project funding? #PowerDelivery #Utilities #Transmission #Substations #Infrastructure #Energy #GridModernization #Construction #TalentAcquisition #Leadership #WorkforceDevelopment #PowerGrid