Essential Elements of a Tech Portfolio

Your portfolio might be missing these underrated elements. Most people focus on polished case studies and pretty visuals. But what actually makes a recruiter pause and think “I want to talk to this person” are the things you don’t usually see. Here are 4 to start adding. 1️⃣ Show your decision trade-offs Don’t just show the final design. Show the fork in the road. What options did you consider, and why did you choose the one you did? Side-by-side screenshots + a short explanation = proof of your critical thinking. 2️⃣ Highlight collaboration moments Portfolios often read like solo projects, but hiring managers want to see you as a teammate. Call out where a PM, dev, or researcher’s input shifted the outcome. Add a quick “before & after” to show the impact of collaboration. 3️⃣ Call out constraints Great design isn’t created in a vacuum. Were you working under a tight deadline? Legacy tech? Limited resources? Own it. Explain how you adapted your solution within the real-world boundaries. That’s what makes your work practical and credible. 4️⃣ Add a “What I’d do differently” section Reflection shows growth. Wrap up each case study with 2–3 quick bullets: what worked, what you’d approach differently, and what you learned. It signals self-awareness without undermining your work. These details don’t just show your work, they show how you work. Now, let’s turn this into a community resource 👇 If you’ve got a portfolio you’re proud of (or one in progress!), drop it in the comments so we can start building a list for visibility and inspiration!

Tired of employers not seeing your value? The "Portfolio Strategy" will fix that (in 7 simple steps): [Context] Companies hire people for one reason: They believe they'll bring the most value to the role. Resumes, cover letters, and LinkedIn are traditional ways to illustrating that value. But they're not the best. If you're struggling to see results with them? You need a portfolio. 1. Choose Your Platform First, choose the place where you'll host your content. I recommend a place that: - Allows you to create the way you want - Maximizes your visibility If you're job searching, it's tough to beat LinkedIn. Medium is another solid option. 2. Identify Your Target Companies Next, brainstorm your list of target companies. You're going to be researching them and creating value that's directly tied to their goals, challenges, and vision. I recommend starting with 3-5. Bonus points if they're in the same industry. 3. Align Your Projects Start with one company. Research the heck out of it from a high level. Then dive deeper into researching the specific product and team you're targeting. Your goal is to identify: - Goals -Challenges - Initiatives Learn as much as you can about them. 3a. Align Your Projects (Examples) Marketer? Perform site audits and recommend 3 ways for companies to get more leads. Software Engineer? QA your favorite apps / tools to identify bugs or improvements. Graphic Designer? Refresh the branding for your favorite products. 4. Map Out The Process Start with your methodology: Why this company / product? Break down your research, brainstorming, and solution process. Find and include reputable data. Project outcomes / ROI if you can. Finally, make a compelling case. Don’t just summarize, sell! 5. Show Your Work Now turn that process into content! Write up a "case study" showing: - The problem / opportunity - How you identified it - Your solution(s) - How you came up with them - The process for implementing them When it's ready, hit publish! 6. Share Your Work Now your case study is out in the world! First, add it to your LinkedIn featured section. Next, break it down into bite sized pieces of content. Start writing posts around: - Your research process - Your solutions process - Insights you came across - Etc 7. Systematize It This works best when you consistently work at it. Create a daily schedule and commit to it. Before you know it, you’ll have a body of work that includes *real* results and clearly illustrates your value. That’s going to get you hired!

For folks who use GitHub and are in early stage careers and hope to add GitHub as a value add to your profile - here is a note. If interviewing for an SDE role, GitHub projects that don't solve a problem and are just a coding exercise are not very helpful. This may sound perplexing but it needs to be said. : Hiring managers and tech leads (like me) look for problem-solvers. A repository full of practice exercises might show you can write code, but it doesn’t demonstrate that you can build impactful solutions. ► How to Make Your Projects Stand Out 1. Frame Them as Solutions: Instead of presenting your project as "just another app," position it as a business solution or a tool that solves a real-world problem. For example: - Instead of “Expense Tracker App,” say, “A tool for freelancers to manage and categorize expenses for tax season.” - Instead of “Weather App,” frame it as, “A weather app optimized for agricultural planning with location-based crop suggestions.” 2. Highlight the Problem It Solves: Every great project starts with a problem. Make it clear what problem you identified and how your project addresses it. - Example: “This tool was designed for small business owners who struggle with automating their daily sales tracking.” 3. Show Quantifiable Value: Numbers tell a story. Include metrics like: - How much time/money the solution saves. - How many users it could potentially impact. - Any test data or feedback you’ve collected. - Example: “This app reduced invoice processing time by 35% in a real-world test case.” 4. Document It Well: A project is only as good as its README. Include: - A brief description of the problem it solves. - Key features. - Instructions on how to run/test it. - Screenshots, GIFs, or a demo link to bring it to life. Having a GitHub full of clone apps or unfinished side projects sends the wrong signal. It doesn’t show creativity, ownership, or impact, it shows you can follow tutorials, and that’s not what companies hire for. Instead, invest your time into one or two high-impact projects that: - Solve real-world problems. - Show off your ability to understand user needs. - Demonstrate your thought process, design skills, and technical execution. So, take a step back, revisit your GitHub, and think: - Does this project solve a problem? - Can I explain its value to someone outside of tech? - Would I hire someone based on this work? If the answer isn’t “yes,” it’s time to rethink how you approach your projects. Remember: One impactful project > 100 clones. Focus on impact, not just output.

𝐓𝐡𝐢𝐧𝐤 𝐘𝐨𝐮𝐫 𝐏𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 𝐃𝐨𝐞𝐬𝐧’𝐭 𝐌𝐚𝐭𝐭𝐞𝐫? 𝐓𝐡𝐢𝐧𝐤 𝐀𝐠𝐚𝐢𝐧, 𝐈𝐭 𝐂𝐨𝐮𝐥𝐝 𝐁𝐞 𝐭𝐡𝐞 𝐊𝐞𝐲 𝐭𝐨 𝐘𝐨𝐮𝐫 𝐍𝐞𝐱𝐭 𝐉𝐨𝐛 𝐈𝐦𝐚𝐠𝐢𝐧𝐞 𝐭𝐡𝐢𝐬: A recruiter is looking at two resumes for a data analyst position. Both candidates have similar skills and experience, but one has a portfolio filled with real-world projects, detailed explanations, and tangible results. Which candidate stands out? When I was starting, I didn’t have a portfolio. I quickly realized that without it, I was missing a crucial opportunity to showcase my work. A strong portfolio isn’t just a collection of projects, it’s your story. It demonstrates how you think, solve problems, and make an impact. Here’s how to build a portfolio that truly shines: 1️⃣ 𝐒𝐡𝐨𝐰 𝐘𝐨𝐮𝐫 𝐁𝐞𝐬𝐭 𝐖𝐨𝐫𝐤: Focus on quality over quantity. Pick 3-5 projects that highlight your skills and have clear, measurable results. Whether it’s a model that improved decisions or a dashboard with impactful insights, each project should tell a story. 2️⃣ 𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐂𝐨𝐧𝐭𝐞𝐱𝐭: Don’t just list what you did, tell why it mattered. What problem were you solving? What was your approach? How did your solution benefit the business or users? This context helps employers see the value you bring. 3️⃣ 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭 𝐘𝐨𝐮𝐫 𝐏𝐫𝐨𝐜𝐞𝐬𝐬: Employers want to know how you think. Detail the steps you took, the tools you used, and any challenges you faced. Did you clean a messy dataset? Choose a specific algorithm? Showing your process sets you apart from others. 4️⃣ 𝐊𝐞𝐞𝐩 𝐈𝐭 𝐀𝐜𝐜𝐞𝐬𝐬𝐢𝐛𝐥𝐞: Make sure your portfolio is easy to navigate. Use a simple layout, and clear headings, and ensure all links work. If it’s a website, make sure it’s mobile-friendly. The easier it is to explore, the more likely it is to impress. Your portfolio is more than just an add-on to your resume, it’s a reflection of your skills, creativity, and attention to detail. In a competitive job market, it could be the difference between landing an interview and being overlooked. If you don’t have a portfolio yet, start building one today. If you have one, review it, does it showcase your best work? If you need feedback or help getting started, I’m here to support you. Found this helpful? Consider re-sharing 🔁 with your network. Follow Mohammed Wasim for more tips, success stories of international students, and data opportunities in US!

If you want a standout portfolio in 2025 as a beginner Data Scientist or AI Engineer, use this framework👇 1. Select a Meaningful Problem → Choose a real-world issue you're genuinely interested in (e.g., climate change prediction, healthcare improvements, social media analytics) → Clearly define the objective and the potential impact of solving this issue 2. Acquire and Document Data → Use reliable sources (Kaggle, UCI Repository, Hugging Face) → Clearly document your process for selecting and gathering the data 3. Data Preparation → Clean and preprocess the data thoroughly → Outline key steps (handling missing data, normalization, feature engineering) 4. Exploratory Data Analysis (EDA) → Generate visualizations and summary statistics → Clearly state insights and how they guide your modeling decisions 5. Select Appropriate Algorithms → Choose suitable methods (e.g., Transformer models, XGBoost, clustering) → Provide reasoning for your choice based on the problem and data 6. Develop and Optimize Your Model → Write clean, reproducible, and modular code → Clearly document model experimentation, model training, hyperparameter tuning, and validation steps 7. Evaluate Your Model → Use relevant metrics (ROC-AUC, F1-score, RMSE, BLEU, MMLU) → Present your evaluations clearly, including visualizations like ROC curves or confusion matrices 8. Analyze Results Critically Clearly interpret outcomes, discuss strengths, limitations, and biases Suggest realistic improvements and next steps 9. Deploy Your Model (Optional) → Create a simple web app using tools like Streamlit, Hugging Face Spaces, Flask, or FastAPI → Provide a working demo and clearly document its functionality 10. Comprehensive Documentation → Write a professional, detailed README. → Clearly summarize your project's purpose, methodology, results, and real-world relevance 11. Let your work talk → Share the code, data catalog, and documentation to reproduce on GitHub → Write a detailed blog about interesting insights and outcomes from the project, and share it on Substack/ Medium/ LinkedIn article You can use this framework to build as many projects as you like. While doing multiple projects make sure to explore different use-cases and different algorithms, which will help you get a holistic view of the Data & ML space. PS: LinkedIn post has character limit, so I will be sharing a list of portfolio projects I would recommend to start with, in the next post -------- Share this with your network ♻️ Follow me (Aishwarya Srinivasan) for more AI insights, news, and educational resources to keep you up-to-date about the AI space!