According to WSJ employers in April added 115,000 jobs as health, leisure and retail drove gains.

Let's hope the trend carries on.

According to WSJ employers in April added 115,000 jobs as health, leisure and retail drove gains.

Let's hope the trend carries on.

According to WSJ employers in April added 115,000 jobs as health, leisure and retail drove gains.

Let's hope the trend carries on in engineering jobs.

According to WSJ employers in April added 115,000 jobs as health, leisure and retail drove gains.

Let's hope the trend carries on.

Heading to Manhattan next weekend and planning to propose to my girlfriend. I’d love a nice spot to celebrate afterward that feels special but isn’t crazy expensive (ideally under $100 per person). Any recommendations?

Three years ago a coworker of mine spent seven months applying to jobs. She was a strong candidate with a decade of project management experience, two industry certifications and a track record that genuinely deserved attention. She heard almost nothing back.

When she finally got a recruiter on the phone through a referral, the recruiter pulled up her resume while they talked. "Your resume is fine," he said. "But you're not using any of the words we search for."

That conversation stuck with me because I work in AI and I understood exactly what he meant. Most people don't.

What is actually happening to your application

When you submit a job application online, your resume almost never goes directly to a recruiter. It goes through software first. Applicant Tracking Systems (used by the vast majority of companies that receive more than a few dozen applications per role) parse every resume automatically, extract keywords and score each application against the job description before a human reviews anything.

The score determines whether you get seen at all.

The critical thing to understand is that this scoring is not evaluating your experience. It is checking whether specific words and phrases from the job description appear in your resume. That is the entire mechanism. The system does not understand context. It does not infer that "managed marketing “campaigns" means you know "demand generation." It does not assume that "led a team" implies "cross-functional leadership." It looks for the exact phrase or it doesn't find it.

This creates a situation where two candidates with identical careers can receive completely different scores based entirely on vocabulary.

Why this is harder to fix than it sounds

The instinctive response is to read the job description and add the missing keywords. Most people try this and it helps but incompletely. There are two reasons.

First, they tend to add keywords to a skills section at the bottom of the resume. ATS systems weight keywords differently depending on where they appear. A term embedded in a bullet point describing an outcome carries more signal than the same term sitting in a list. Recruiters who read past the automated filter also respond better to keywords in context rather than appended to a skills list that reads like it was written by a robot.

Second, identifying which specific phrases the system is actually scanning for is harder than it looks. Job descriptions use language inconsistently.

One posting says "stakeholder management," another says "stakeholder engagement" and a third says "cross-functional communication." These mean the same thing. The ATS treats them as different terms. Knowing which variant to use requires reading the posting very carefully or having a tool that does the extraction for you.

What actually moves your score

The vocabulary shift that matters most is moving from describing duties to describing outcomes using the language of the role. Compare these two bullets:

Before: Managed a team responsible for product launches.

After: Led cross-functional delivery of six product launches across engineering, marketing and operations, shipping on schedule in five of six cycles.

The second bullet contains four phrases that commonly appear in product management job descriptions: "cross-functional delivery," "engineering, marketing and operations," "product launches" and implicitly "stakeholder alignment" through the coordination described. The first bullet contains almost none of them.

The experience described is identical. The ATS score is not.

How to find the specific gaps in your own resume

Reading job descriptions carefully and doing this comparison manually is slow but works.

Whichever method you use, the work is the same: identify the vocabulary the job description uses for skills you actually have and update your bullets to reflect that language. Not by stuffing keywords into a list at the bottom but by rewriting the bullets themselves so the terms appear in the context of real outcomes.

The broader point

My colleague's problem was not her experience. It was that she described ten years of cross-functional program delivery using language that matched none of the postings she was applying to. Once she understood that, she rewrote four bullets and her response rate changed within two weeks.

ATS optimization is not about gaming a system or misrepresenting your background. It is about describing what you actually did using the same vocabulary the industry uses to describe it. The gap between those two things is smaller than most people think and closing it is mostly a matter of knowing it exists.

The resume is a gatekeeper, not a job offer — and there are several ways around it.

What else you can do when the resume isn't working and that deserves a direct answer.

Referrals are the single highest-conversion path.

Most hiring managers receive referrals from trusted colleagues before a posting even goes live. A referred candidate skips ATS screening entirely and enters the process with implicit credibility. The data consistently shows referred candidates are hired at 3–4x the rate of cold applicants.

This doesn't require knowing the right people — it requires asking. Reach out to former colleagues, classmates, and professional contacts and be direct: "I'm actively looking for roles in X. If you hear of anything or know someone worth talking to, I'd genuinely appreciate an introduction."

Most people are willing to help if you make it easy for them.

Go around the resume, not through it.

For roles where your resume is the weak point, consider approaches that let your work speak before your document does:

- Build something visible. A portfolio, GitHub repository, case study, or published piece of work gives a hiring manager something to evaluate that isn't your resume. In creative, technical, and analytical roles especially, demonstrated output outweighs a weak resume.

- Write publicly. A Substack, LinkedIn article, or detailed answer on a platform like this one establishes expertise in ways a two-page document cannot. Several people have been hired based on a single piece of writing that reached the right person.

- Attend industry events. In-person or virtual events within your target industry create conversations that convert to introductions. A brief genuine conversation at a conference is worth more than twenty cold applications.

Target smaller companies deliberately.

Large employers run every application through ATS software. Companies under 50 people typically don't — a hiring manager reads your resume directly.

Your chances of a real human evaluation increase substantially, and the feedback loop is faster if you're not a fit.

Use recruiters strategically.

Agency recruiters — particularly specialist ones in your field — have direct relationships with hiring managers and can place your profile in front of decision-makers without a resume ever hitting an ATS. They are motivated to place you, so they will also tell you honestly what's weak about your presentation. This is free feedback that most people don't take advantage of.

Contract or freelance work first.

Taking on a short-term project or contract role at a company you want to work for full-time is one of the most underused strategies. It removes all the friction of the hiring process and lets your actual work make the case. A significant proportion of full-time hires at smaller companies started as contractors.

These are the most commonly scanned keywords in investment banking and capital markets job postings. Check how many appear in your resume.

Transaction Types

M&A mergers and acquisitions LBO leveraged buyout IPO initial public offering restructuring debt financing equity financing capital markets

Financial Modeling & Valuation

DCF dscounted cash flow LBO model merger model comparable company analysis comps precedent transactions accretion/dilution financial modeling valuation

Capital Markets

ECM equity capital markets DCM debt capital markets syndication roadshow book building high-yield bonds investment grade convertible notes

Due Diligence & Deal Execution

due diligence data room CIM confidential information memorandum LOI letter of intent term sheet purchase price allocation representations and warranties

Financial Metrics & Returns

EBIT DAEV/EBITDA enterprise value IRR MOIC free cash flow FCF leverage ratio net debt returns analysis

Pitch & Client Development

pitch book pitch deck client coverage deal origination origination mandates league table advisory buy-side sell-side

Tools & Databases

Bloomberg Terminal Capital IQ CapI Q Fact Set Refinitiv Excel financial modeling PowerPoint PitchBook

Credentials & Regulatory

Series 7 Series 63 Series 79 FINRA CFA SEC prospectus S-1 securities regulation

These are the most commonly scanned keywords in performance marketing and paid media job postings. Check how many appear in your resume.

Paid Search (SEM)

Google Ads Microsoft Advertising Bing Ads PPC SEM Smart Bidding Performance Max Quality Score keyword bidding search engine marketing

Paid Social

Meta Ads Facebook Ads Instagram Ads TikTok Ads LinkedIn Ads Pinterest Ads Advantage+ Advantage+Shopping paid social

Performance Metrics & KPIs

ROAS CPA CPL CAC LTV CTR CVR MER blended ROAS CPM marketing efficiency ratio

Attribution & Analytics

Google Analytics-4 GA4 Google Tag Manager multi-touch attribution incrementality testing media mix modeling Northbeam Triple WhaleUTM tracking

Conversion Rate Optimization

A/B testing CRO conversion rate optimization landing page optimization multivariate testing OptimizelyVWO heatmaps

Programmatic & Display

programmatic advertising DV360 The Trade Desk DSP retargeting prospecting lookalike audiences display advertising

Email & Lifecycle Marketing

Klaviyo HubSpot email automation drip campaigns segmentation deliverability lifecycle marketing retention

Data & Reporting

SQL Looker Tableau Google Data Studio Looker Studio cohort analysis funnel analysis LTV modeling

Heading to San Francisco this weekend and planning to propose to my girlfriend. I’d love a nice spot to celebrate afterward that feels special but isn’t crazy expensive (ideally under $100 per person). Any recommendations?

These are the most commonly scanned keywords across AI engineer job postings in 2026. Check how many appear in your resume.

LLM Frameworks & Orchestration

LangChain LlamaIndex LangGraph AutoGen CrewAI Haystack Semantic Kernel Flowise

Foundation Models & APIs

OpenAI API Anthropic Claude GPT-4o LLaMA-3 Mistral Gemini Cohere Ollama

Vector Databases & Embeddings

Pinecone Weaviate Chroma pgvector FAISS Qdrant Milvus Elasticsearch

RAG & Knowledge Retrieval

RAG Retrieval Augmented Generation semantic search hybrid search reranking chunking embedding models knowledge graphs

AI Agent Systems

AI agents function calling tool use multi-agent systems ReAct agentic workflows Model Context Protocol

Prompt Engineering

prompt engineering few-shot prompting chain-of-thought system prompts structured outputs prompt chaining guardrails

Fine-tuning & Alignment

LoRAQLoRAPEFTfine-tuninginstruction tuningDPORLHF

Evaluation & Observability

RAGAS LangSmith LLM evaluation Weights & Biases Arize Phoenixe vals benchmarking Helicone

MLOps & Compute Platforms

Hugging Face PyTorch vLLM AWS SageMaker Azure AI Studio Vertex AI TensorRT-LLM

Python & Data Stack

Python FastAPI asyncio pydantic REST APIs streaming NumPy pandas

The most commonly scanned keywords in ML engineering and AI job postings.

ML Frameworks

PyTorch TensorFlow Keras scikit-learn XGBoost LightGBM HuggingFace JAX

MLOps & Infrastructure

MLflow Kubeflow Apache Airflow DVC feature store model registry model serving BentoML

Cloud & Compute

AWS SageMaker Google Vertex AI Azure ML CUDA GPU training distributed training Apache SparkRay

Model Development

LLMs large language models transformers RLHF RAG fine-tuning model evaluation A/B testing

Data Engineering

feature engineering data pipelines ETL Apache Kafka data versioning training data label management data preprocessing

Languages & Tools

Python SQL Docker Kubernetes Git Jupyter CI/CD REST APIs

These are the most commonly scanned keywords in investment banking and capital markets job postings. Check how many appear in your resume.

Transaction Types

M&A mergers and acquisitions LBO leveraged buyout IPO initial public offering restructuring debt financing equity financing capital markets

Financial Modeling & Valuation

DCF dscounted cash flow LBO model merger model comparable company analysis comps precedent transactions accretion/dilution financial modeling valuation

Capital Markets

ECM equity capital markets DCM debt capital markets syndication roadshow book building high-yield bonds investment grade convertible notes

Due Diligence & Deal Execution

due diligence data room CIM confidential information memorandum LOI letter of intent term sheet purchase price allocation representations and warranties

Financial Metrics & Returns

EBIT DAEV/EBITDA enterprise value IRR MOIC free cash flow FCF leverage ratio net debt returns analysis

Pitch & Client Development

pitch book pitch deck client coverage deal origination origination mandates league table advisory buy-side sell-side

Tools & Databases

Bloomberg Terminal Capital IQ CapI Q Fact Set Refinitiv Excel financial modeling PowerPoint PitchBook

Credentials & Regulatory

Series 7 Series 63 Series 79 FINRA CFA SEC prospectus S-1 securities regulations

I’m sure this might get some pushback, but honestly, we’re living in a time where AI is part of everyday life—whether it’s for work or personal stuff.

For me, one thing that’s made a real difference is customizing my resume for each job I apply to. I’ve noticed I get way more callbacks compared to when I used to just send the same generic version everywhere. It takes a bit more effort, but it’s been worth it.

Digital marketing manager roles require the broadest keyword profile — cross-channel ownership, attribution, and a blend of execution and strategy terms. ATS for these roles is typically configured to screen for 3–5 specific channel tools alongside leadership indicators.

CHANNELS & STRATEGY

integrated digital marketing omnichannel strategy demand generation inbound marketing growth marketing digital strategy campaign management performance marketing brand awareness

ANALYTICS & REPORTING

Google Analytics 4GA4 attribution modelling multi-touch attribution marketing dashboard KPI reporting ROAS CAC CLV MQLs SQLs funnel analysis

TOOLS & PLATFORMS

HubSpot Salesforce Marke to Google AdsMeta Ads LinkedIn AdsLooker Tableau Semrush Ahrefs

I’m sure this might get some pushback, but honestly, we’re living in a time where AI is part of everyday life—whether it’s for work or personal stuff.

For me, one thing that’s made a real difference is customizing my resume for each job I apply to. I’ve noticed I get way more callbacks compared to when I used to just send the same generic version everywhere. It takes a bit more effort, but it’s been worth it.

I’m sure this might get some pushback, but honestly, we’re living in a time where AI is part of everyday life—whether it’s for work or personal stuff.

For me, one thing that’s made a real difference is customizing my resume for each job I apply to. I’ve noticed I get way more callbacks compared to when I used to just send the same generic version everywhere. It takes a bit more effort, but it’s been worth it.

I’m sure this might get some pushback, but honestly, we’re living in a time where AI is part of everyday life—whether it’s for work or personal stuff.

For me, one thing that’s made a real difference is customizing my resume for each job I apply to. I’ve noticed I get way more callbacks compared to when I used to just send the same generic version everywhere. It takes a bit more effort, but it’s been worth it.

I’m sure this might get some pushback, but honestly, we’re living in a time where AI is part of everyday life—whether it’s for work or personal stuff.

For me, one thing that’s made a real difference is customizing my resume for each job I apply to. I’ve noticed I get way more callbacks compared to when I used to just send the same generic version everywhere. It takes a bit more effort, but it’s been worth it.