Preparing for Job Interviews

You're in a job interview, you get the offer—but the salary? Way lower than expected. The worst move? Accepting on the spot. The second worst? Declining outright. Here's how you can take the 'ick' out of negotiating: 1. Start with Gratitude →“Thank you for the offer.” 2. Share Excitement →“I’m really excited about the role and joining the company.” 3. Address the Salary →“Before I accept, I’d like to discuss the salary. It’s below what I believe reflects the market value for my experience.” 4. Reinforce Your Value →“I’m confident my expertise in A and B, and my contributions to C and D will drive success here.” 5. Reiterate Market Value →“Based on my research and track record, I believe a salary range of X to Y would be more in line with the industry.” Where to do research? Check salary data on sites like Glassdoor, Payscale, and LinkedIn, or ask industry peers and recruiters for real-world insights. Pro tip: Use multiple sources to get a well-rounded view and always adjust for location and years of experience. P.S. Have you ever accepted a salary because you didn't know how to negotiation? I'll go first: Yes, I have...

I’ve reviewed > 400 portfolios this year. Observation #1: The ones that got interviews weren’t the prettiest. They were the clearest. → Clear intent (what roles they’re targeting) → Clear structure (who they helped + what changed) → Clear thinking (how they made decisions) Observation #2: Hiring managers responded best to portfolios that made it easy to scan, not admire. → 3-5 second headlines that told the story → Metrics up top, visuals in the middle, lessons at the end → Less storytelling. More signal. Observation #3: The portfolios that ‘failed’? → Opened with “Hi, I’m Alex and I love solving problems” → Contained 30+ screenshots with no explanation → Didn’t articulate business impact or their role → Had no opinion, no POV, no process If I were applying today? → I’d restructure my case studies to lead with outcomes → I’d add a design philosophy section to show how I think → I’d cut 40% of the fluff and focus on what actually matters → I’d communicate my USP and elevator pitch up front Your portfolio isn’t a gallery. It’s a business case for why you’re worth hiring. ----- Just thought I'd share this after reviewing some notes over the weekend. Hope it helps! ----- #ux #tech #design #ai #business #careers

Mechanical, hardware, and chemical engineers are among the hardest-to-fill/hardest-to-hire roles for climate tech companies, with time-to-fill times longer than even machine learning engineering roles. ClimateTechList teamed up with data scientist/engineer Jason Zou to analyze our dataset of ~60,000 job posts from 900 climate tech companies posted in the last 6 months. Specifically, we found that the time-to-fill for the following roles were: - Sales: 31.9 days - Marketing: 35.9 - Analyst: 36.0 - Design: 38.5 - Data Science: 40.3 - Product Management: 41.5 - Operations: 42 - Electrical Engineer: 47.1 - Software Eng: 48.2 - Machine Learning Eng: 48.3 - Mechanical Eng: 49.0 - Hardware Eng: 50.2 - Chemical Eng: 51.5 Engineering jobs associated with physical production are hard to hire, namely mechanical engineering, hardware engineering, and chemical engineering, all of which take almost 2x as long to fill (50 days) as sales jobs. Even machine learning engineering positions, in high demand from the AI boom, are filled at a slightly faster rate than these 3 positions Possible reasons for this effect - many of these jobs require in-person work, which makes job matching jobs to candidates inherently more difficult - Federal legislation of the last few years- Bipartisan Infrastructure Law, Inflation Reduction Act, CHIPS Act are all driving massive investments into U.S. physical infrastructure and manufacturing. These investments disproportionally require talent with physical-product engineering skills more than software engineering skills. 👉 For more insights on hiring trends by company, country and climate tech vertical, see our latest climate tech hiring trends report here: https://lnkd.in/gpMCaSZ6 #climatetechlist #decarbonization #energytransition #chemicalengineering #mechanicalengineering #hardwareengineering #hiringtrends

Your competence at work is judged in seconds. Even when you over-deliver, you can be underestimated. Every day, false assumptions about you are made: — Polite = Weak — Older = Not agile — A foreign accent = Less capable — Introverted =  Not a strong leader — Woman =  Softer voice, less authority It's not just unfair. It's exhausting. So the question is: How do you beat biases without changing who you are? Here’s what I recommend: 𝟭. 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝘁𝗵𝗲 𝗻𝗮𝗿𝗿𝗮𝘁𝗶𝘃𝗲 → Speak about impact, not effort. → Articulate your value proposition. →“Here’s the problems I solve. Here's how. Here’s the result."  If no one knows what you bring to the table, they won’t invite you to it. 𝟮. 𝗩𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗶𝘀 𝗽𝗼𝘄𝗲𝗿 Silent excellence is wasted potential. → Speak up when it feels risky. → Build real not just strategic relationships. → Share insights where people are paying attention. You don’t need to be loud. You need to be seen. 𝟯. 𝗧𝘂𝗿𝗻 𝘆𝗼𝘂𝗿 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 𝗶𝗻𝘁𝗼 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗶𝗮𝘁𝗼𝗿𝘀 The traits that trigger assumptions? Those are your edge. → Introverted? That’s deep listening. → Accent? That’s global perspective. Don’t flatten yourself to fit. Distinguish yourself to lead. 𝟰. 𝗢𝘄𝗻 𝘆𝗼𝘂𝗿 𝗽𝗿𝗲𝘀𝗲𝗻𝗰𝗲 → Say “I recommend” not "I think.” → Hold eye contact. Take up space. → Act like your presence belongs (even when others haven’t caught up.) Confidence isn’t volume. It’s grounding. Bias is everywhere. But perception can be changed. Don't let other people's false assumptions define you. Do you agree? ➕ Follow Deena Priest for strategic career insights. 📌Join my newsletter to build a career grounded in progress, peace and pay.

After taking 75 Software Engineer interviews at Google in < 7 months, I’ve seen a range of mistakes all of us make in coding interviews. Here’s a compiled list to help you (and me) avoid these pitfalls in our future interviews! 1️⃣ Not Clarifying Requirements > Many candidates jump straight into coding. Often without fully understanding the problem. This can waste time and lead to errors. Tip: Always ask clarifying questions. To ensure you get the requirements. Confirm edge cases and input constraints early on. 2️⃣ Overcomplicating Solutions > In the heat of the moment, it is easy to overthink a problem. And this complicates the solution, both for you and your interviewer. Tip: Start with a brute-force approach (just explain it), then iterate towards optimization (code it up). Easy-to-understand solutions get bonus points. 3️⃣ Under-Communication > Interviews are not just about coding. They’re also about conveying your thought process. Silence takes away the only help you have during the interview—your interviewer. Tip: Think out loud! Explain your reasoning and approach as you code. This helps the interviewers understand you and even guide you if needed. 4️⃣ Ignoring Edge Cases > Many candidates create a working solution. But fail to consider edge cases. This can lead to catastrophic failures. Tip: After arriving at a solution, always discuss potential edge cases. Explain how your code handles them. This shows your thoroughness. 5️⃣ Neglecting to Optimize > Even if your solution works, failing to consider optimization can cost you points. Tip: After solving the problem, re-read your solution and discuss ways to improve time and space complexity. No micro-optimizations. Interviewers appreciate candidates who think about efficiency in big-oh notation. 6️⃣ Skipping Dry Runs > 80%+ candidates skip the dry run of their code, leading to overlooked mistakes. Tip: Walk through your code with sample inputs. This helps catch errors early and makes you look proactive. 7️⃣ Getting Flustered > Interviews are stressful. And it is easy to panic if you hit a roadblock. Tip: If you’re stuck, ask for a minute or 2 to gather your thoughts. Ask for hints if necessary—interviewers appreciate candidates who are willing to seek help. Those were my 2 cents on how to tackle coding interviews. But believe it or not, the best way to realize your interview mistakes would be to start taking interviews (even mock ones). After conducting so many interviews at Google, I realized how I often fell into the same traps as everyone. Like going completely silent or forgetting to do a dry run for the interviewer. Taking interviews altered my perspective, and now I advise everyone preparing for interviews to take a couple of them first. Total game changer! #codingInterviews #jobPrep #softwareEngineering #Google #interviewTips

One of the most common questions in Data Analyst interviews is: "Tell me about an analytics project you've worked on recently." Many candidates stumble here— not because their projects aren't good — but because they lack clarity and structure while explaining. Here’s a simple and effective structure you can use—it's called the STAR method (Situation, Task, Action, Result): 𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐒𝐢𝐭𝐮𝐚𝐭𝐢𝐨𝐧 (𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭): Start by clearly describing the problem your project addresses. Example: "The company I worked with faced a major issue—customer churn increased significantly (about 20%) in just 6 months, directly impacting revenue." Highlight the Impact: Clearly discuss why solving this problem was crucial for the business. Example: "Due to this churn, monthly revenue dropped by nearly 15%, and customer acquisition costs increased." 𝐘𝐨𝐮𝐫 𝐓𝐚𝐬𝐤 (𝐑𝐨𝐥𝐞 & 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲): Briefly explain what your specific role was in this project. Example: "My responsibility was to analyze customer behavior, identify churn patterns, and suggest actionable insights to reduce churn." 𝐀𝐜𝐭𝐢𝐨𝐧 (𝐘𝐨𝐮𝐫 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡): Here’s where you showcase your analytical thinking and technical skills clearly: Explain your data collection methods and sources (SQL queries, surveys, databases). Briefly describe data cleaning and preparation (Excel, Python-Pandas, SQL). Mention clearly your analytical techniques (Segmentation, Cohort analysis, statistical tests, ML algorithms). Highlight tools used for visualization (Power BI, Tableau). Example: "I extracted and cleaned historical customer data using SQL & Python (Pandas). Then, I conducted cohort analysis and customer segmentation to identify patterns in churn behavior. Finally, I built a detailed interactive dashboard in Power BI to present my findings." 𝐑𝐞𝐬𝐮𝐥𝐭𝐬 (𝐂𝐥𝐞𝐚𝐫 𝐎𝐮𝐭𝐜𝐨𝐦𝐞): Conclude your explanation by highlighting measurable outcomes: Clearly explain business impact. Share measurable metrics (percentage improvements, revenue increase/decrease, cost savings). Example: "By applying recommendations from my analysis, the churn rate decreased by about 12% over three months, directly saving approximately ₹30 lakhs in revenue. The insights also led to improved customer retention strategies." 𝐄𝐧𝐝 𝐖𝐢𝐭𝐡 𝐖𝐡𝐚𝐭 𝐘𝐨𝐮 𝐋𝐞𝐚𝐫𝐧𝐞𝐝 (𝐎𝐩𝐭𝐢𝐨𝐧𝐚𝐥 𝐛𝐮𝐭 𝐢𝐦𝐩𝐚𝐜𝐭𝐟𝐮𝐥): A quick sentence on key learnings or challenges makes your explanation genuine and engaging. Example: "This project taught me the importance of aligning analytics solutions with real business goals, rather than just technical outputs." Remember, your interviewer is not only evaluating your technical skills—they're also assessing your problem-solving capabilities, clarity in communication, and understanding of the business context. Share your own experiences and tips in the comments! Let's learn and grow together. Follow Shakra Shamim for more such posts !!

Do you know your unique selling point or your customer’s reason to buy? You should. Knowing how you compare to the competition and stand out is essential for strong positioning. Positioning is essential for every product and service for which the customers have an alternative. It means identifying which valuable characteristics your offerings have compared to the main alternatives. Without positioning, customers have no reason to buy from you. After all, if you don’t stand out positively in any way, why would they buy from you? There are many approaches to positioning, Michael Porter’s Five Forces Framework and Generic Strategies being the most famous of them. While Porter’s approach helps finding out WHAT your positioning could or should be, there is little information as to HOW to do it. This is where April Dunford’s approach to positioning comes in. In her book, “Obviously Awesome” she lays out a practical, five-plus-one-component approach to positioning. The components are: 1. Competitive Alternatives If you didn’t exist, what would customers use? 2. Unique Attributes What features/attributes do you have that alternatives do not? 3. Value What value do the attributes enable for customers? 4. Customers that Care Who cares a lot about that value? 5. Market you Win What context makes the value obvious to your target segments? 6. Relevant Trends (Bonus)  What trends make your product relevant right now? There’s a couple of things I like about Dunford’s approach: 👉 It doesn’t start with thoroughly analyzing the customer’s needs and not even start with the product or market. 👉 It starts with how customers currently fulfill their needs. Whatever the problem, customers have some solution right now (otherwise the problem wouldn’t be a problem they would need a solution for…). 👉 It only moves to the product or service category in component 5. This means that picking what you call the product or service comes after establishing its unique and value-adding attributes. 👉 It helps bringing in current trends at the right place. Not at the start, which would merely lead to chasing hypes, but as a way to enhance the product or service’s relevance for the customer right now. While seemingly simple, this makes it one of the more intelligent approaches to positioning out there. Time to look at your positioning. Do you use all six components, and do you use them in the right order and way? #targetaudience #marketingdevelopment #productdevelopment

Ever wondered how much your profile picture influences your career opportunities? Harvard's research ("Look the Part? The Role of Profile Pictures in Online Labor Markets") by Isamar Troncoso and Lan Luo sheds light on an intriguing aspect of our professional lives - the impact of profile pictures on hiring decisions. Here's a quick digest: • Profile Picture Influence: Your photo could be swaying hiring decisions more than your skills. • Reputation vs. Appearance: Lack of clear differentiators in profiles? Appearances might be filling the gap. • Performance Disconnect: Looking the part doesn’t always mean performing the part. • Beyond the Visuals: Perceived job fit affects decisions, and platform suggestions can't fully counteract this bias. Now, let's think about this: What message does our profile picture on LinkedIn or a resume send? Is it possibly influencing perceptions in ways we hadn’t considered? Here’s my take: • Resumes Without Pictures: Let's value skills and experiences over appearances. • Minimal Personal Info: Reducing personal details can curb unconscious bias. • True Self on Social Media: Craft your LinkedIn to reflect your authentic professional self, not just what you think others want to see, but be aware of potential biases. What changes will you make to your online profile after knowing this? #inclusivehiring #talentattraction #unconsciousbias

I’ve been interviewing candidates for a new role and there’s one thing I’ve seen 90% of them struggle with: sharing the story of their career achievements. But don’t worry—I’ve got a simple hack that can help you overcome it: ✏️ Create a monthly ritual to review and document every significant work win, and turn each into a mini-case study. Documenting your wins regularly will save you HOURS when you prep for your next interview—plus it’s great fodder for: ⤷ your annual performance review ⤷ your 1x1s with your manager ⤷ your resume Here’s my 3-step process: 1️⃣ Weekly Check-in: Turn work ➡️ wins ⤷ Start a weekly habit of documenting your wins (grab my free template in the comments). ⤷ Block 30 minutes on your calendar every Friday to hold yourself accountable. ⤷ Ask yourself, “What did I accomplish this week that moved the needle?”   2️⃣ Monthly Recap: Turn wins ➡️ headlines ⤷ Identify 1–2 significant achievements and summarize them using this formula: [Action Verb] + [Specific Metric] + [Timeframe] + [Business Impact] ⤷ Make a bullet-point list (so you can stay organized and repurpose it for your resume later!) ⤷ Include dates and timelines for your own records—you’ll use them in step 3.   3️⃣ Quarterly Story-Building: Headlines ➡️ stories ⤷ Identify your top 3 quarterly wins. ⤷ Start a fresh document and map out each of those wins using the STAR method: ️ ⭐ Situation: What was the context? ️⭐ Task: What was your specific responsibility? ⭐ Action: What steps did you take? ⭐ Result: What measurable outcome did you achieve? ⤷ Ask AI to help you share that information as a story. Here’s the prompt I like to use: ✍ Can you help me turn this achievement into a story using the STAR framework for an upcoming interview for a [title here] role? Please keep it concise. [paste win]   Here’s what this looks like in action 👇 ⤷ Weekly win: March ’23 → Decreased CPA by 28% & increased conversion by 15% ⤷ Monthly recap: Optimized paid search campaigns in March 2023 that decreased CPA by 28% while increasing conversions by 15%, resulting in higher profit margins for the company. ⤷ Quarterly story: When I joined the marketing team in January 2023, our paid search campaigns were generating leads but at a high CPA, with budget constraints approaching in Q2.I was tasked with reducing CPA without sacrificing lead volume. In March 2023, I audited our campaigns and implemented three key changes: restructured ad groups with tightly-themed keywords, refined match types with strategic negative keywords, and A/B tested value-focused ad copy. By month-end, these optimizations decreased cost-per-acquisition by 28% while increasing conversion volume by 15%, saving budget and creating a scalable framework for future campaigns. What are your tips for storytelling in your interviews? I’d love to hear them. 

The “Big Beautiful Bill” just changed the game for tech startups. What happened? Since 2022, startups couldn’t deduct engineering salaries in the year incurred. Instead, these costs had to be spread over 5 years. For pre-revenue companies burning cash on engineering talent, this created phantom profits and real tax bills. Now, with R&D expenses fully deductible again, three immediate impacts for startups: * Cash flow relief: No more tax bills on money you haven’t made yet. This directly translates to runway extension - critical oxygen for startups. * Domestic hiring becomes viable again: Many startups reluctantly offshored development to avoid tax exposure. U.S. engineering talent is back on the table as a strategic option. * Hiring acceleration: Expect seed and Series A companies to ramp up technical recruiting now that the tax penalty is gone. What I’m watching for next: * Senior U.S. engineering salaries trending upward * A surge in early-stage startup hiring * Enterprise companies scrambling to retain talent as nimble startups become more aggressive The companies that move fastest will capture the best talent. If you’re leading engineering at a startup, now is the time to revisit your hiring roadmap and talent strategy. Are you planning to accelerate engineering hiring because of this change? What positions are suddenly back on your radar? #StartupStrategy #EngineeringLeadership #TechHiring #BBBEffect