scrapbook
  • "Unorganized" Notes
  • The Best Public Datasets for Machine Learning and Data Science
  • Practice Coding
  • plaid-API project
  • Biotech
    • Machine Learning vs. Deep Learning
  • Machine Learning for Computer Graphics
  • Books (on GitHub)
  • Ideas/Thoughts
  • Ziva for feature animation: Stylized simulation and machine learning-ready workflows
  • Tools
  • 🪶math
    • Papers
    • Math for ML (coursera)
      • Linear Algebra
        • Wk1
        • Wk2
        • Wk3
        • Wk4
        • Wk5
      • Multivariate Calculus
    • Improving your Algorithms & Data Structure Skills
    • Algorithms
    • Algorithms (MIT)
      • Lecture 1: Algorithmic Thinking, Peak Finding
    • Algorithms (khan academy)
      • Binary Search
      • Asymptotic notation
      • Sorting
      • Insertion sort
      • Recursion
      • Solve Hanoi recursively
      • Merge Sort
      • Representing graphs
      • The breadth-first search algorithm
      • Breadth First Search in JavaScript
      • Breadth-first vs Depth-first Tree Traversal in Javascript
    • Algorithms (udacity)
      • Social Network
    • Udacity
      • Linear Algebra Refresher /w Python
    • math-notes
      • functions
      • differential calculus
      • derivative
      • extras
      • Exponentials & logarithms
      • Trigonometry
    • Probability (MIT)
      • Unit 1
        • Probability Models and Axioms
        • Mathematical background: Sets; sequences, limits, and series; (un)countable sets.
    • Statistics and probability (khan academy)
      • Analyzing categorical data
      • Describing and comparing distributions
      • Outliers Definition
      • Mean Absolute Deviation (MAD)
      • Modeling data distribution
      • Exploring bivariate numerical data
      • Study Design
      • Probability
      • Counting, permutations, and combinations
      • Binomial variables
        • Binomial Distribution
        • Binomial mean and standard deviation formulas
        • Geometric random variable
      • Central Limit Theorem
      • Significance Tests (hypothesis testing)
    • Statistics (hackerrank)
      • Mean, Medium, Mode
      • Weighted Mean
      • Quartiles
      • Standard Deviation
      • Basic Probability
      • Conditional Probability
      • Permutations & Combinations
      • Binomial Distribution
      • Negative Binomial
      • Poisson Distribution
      • Normal Distribution
      • Central Limit Theorem
      • Important Concepts in Bayesian Statistics
  • 📽️PRODUCT
    • Product Strategy
    • Product Design
    • Product Development
    • Product Launch
  • 👨‍💻coding
    • of any interest
    • Maya API
      • Python API
    • Python
      • Understanding Class Inheritance in Python 3
      • 100+ Python challenging programming exercises
      • coding
      • Iterables vs. Iterators vs. Generators
      • Generator Expression
      • Stacks (LIFO) / Queues (FIFO)
      • What does -1 mean in numpy reshape?
      • Fold Left and Right in Python
      • Flatten a nested list of lists
      • Flatten a nested dictionary
      • Traverse A Tree
      • How to Implement Breadth-First Search
      • Breadth First Search
        • Level Order Tree Traversal
        • Breadth First Search or BFS for a Graph
        • BFS for Disconnected Graph
      • Trees and Tree Algorithms
      • Graph and its representations
      • Graph Data Structure Interview Questions
      • Graphs in Python
      • GitHub Repo's
    • Python in CG Production
    • GLSL/HLSL Shading programming
    • Deep Learning Specialization
      • Neural Networks and Deep Learning
      • Untitled
      • Untitled
      • Untitled
    • TensorFlow for AI, ML, and DL
      • Google ML Crash Course
      • TensorFlow C++ API
      • TensorFlow - coursera
      • Notes
      • An Introduction to different Types of Convolutions in Deep Learning
      • One by One [ 1 x 1 ] Convolution - counter-intuitively useful
      • SqueezeNet
      • Deep Compression
      • An Overview of ResNet and its Variants
      • Introducing capsule networks
      • What is a CapsNet or Capsule Network?
      • Xception
      • TensorFlow Eager
    • GitHub
      • Project README
    • Agile - User Stories
    • The Open-Source Data Science Masters
    • Coding Challenge Websites
    • Coding Interview
      • leetcode python
      • Data Structures
        • Arrays
        • Linked List
        • Hash Tables
        • Trees: Basic
        • Heaps, Stacks, Queues
        • Graphs
          • Shortest Path
      • Sorting & Searching
        • Depth-First Search & Breadth-First Search
        • Backtracking
        • Sorting
      • Dynamic Programming
        • Dynamic Programming: Basic
        • Dynamic Programming: Advanced
    • spaCy
    • Pandas
    • Python Packages
    • Julia
      • jupyter
    • macos
    • CPP
      • Debugging
      • Overview of memory management problems
      • What are lvalues and rvalues?
      • The Rule of Five
      • Concurrency
      • Avoiding Data Races
      • Mutex
      • The Monitor Object Pattern
      • Lambdas
      • Maya C++ API Programming Tips
      • How can I read and parse CSV files in C++?
      • Cpp NumPy
    • Advanced Machine Learning
      • Wk 1
      • Untitled
      • Untitled
      • Untitled
      • Untitled
  • data science
    • Resources
    • Tensorflow C++
    • Computerphile
      • Big Data
    • Google ML Crash Course
    • Kaggle
      • Data Versioning
      • The Basics of Rest APIs
      • How to Make an API
      • How to deploying your API
    • Jupiter Notebook Tips & Tricks
      • Jupyter
    • Image Datasets Notes
    • DS Cheatsheets
      • Websites & Blogs
      • Q&A
      • Strata
      • Data Visualisation
      • Matplotlib etc
      • Keras
      • Spark
      • Probability
      • Machine Learning
        • Fast Computation of AUC-ROC score
    • Data Visualisation
    • fast.ai
      • deep learning
      • How to work with Jupyter Notebook on a remote machine (Linux)
      • Up and Running With Fast.ai and Docker
      • AWS
    • Data Scientist
    • ML for Beginners (Video)
    • ML Mastery
      • Machine Learning Algorithms
      • Deep Learning With Python
    • Linear algebra cheat sheet for deep learning
    • DL_ML_Resources
    • Awesome Machine Learning
    • web scraping
    • SQL Style Guide
    • SQL - Tips & Tricks
  • 💡Ideas & Thoughts
    • Outdoors
    • Blog
      • markdown
      • How to survive your first day as an On-set VFX Supervisor
    • Book Recommendations by Demi Lee
  • career
    • Skills
    • learn.co
      • SQL
      • Distribution
      • Hypothesis Testing Glossary
      • Hypothesis Tests
      • Hypothesis & AB Testing
      • Combinatorics Continued and Maximum Likelihood Estimation
      • Bayesian Classification
      • Resampling and Monte Carlo Simulation
      • Extensions To Linear Models
      • Time Series
      • Distance Metrics
      • Graph Theory
      • Logistic Regression
      • MLE (Maximum Likelihood Estimation)
      • Gradient Descent
      • Decision Trees
      • Ensemble Methods
      • Spark
      • Machine Learning
      • Deep Learning
        • Backpropagation - math notation
        • PRACTICE DATASETS
        • Big Data
      • Deep Learning Resources
      • DL Datasets
      • DL Tutorials
      • Keras
      • Word2Vec
        • Word2Vec Tutorial Part 1 - The Skip-Gram Model
        • Word2Vec Tutorial Part 2 - Negative Sampling
        • An Intuitive Explanation of Convolutional Neural Networks
      • Mod 4 Project
        • Presentation
      • Mod 5 Project
      • Capstone Project Notes
        • Streaming large training and test files into Tensorflow's DNNClassifier
    • Carrier Prep
      • The Job Search
        • Building a Strong Job Search Foundation
        • Key Traits of Successful Job Seekers
        • Your Job Search Mindset
        • Confidence
        • Job Search Action Plan
        • CSC Weekly Activity
        • Managing Your Job Search
      • Your Online Presence
        • GitHub
      • Building Your Resume
        • Writing Your Resume Summary
        • Technical Experience
      • Effective Networking
        • 30 Second Elevator Pitch
        • Leveraging Your Network
        • Building an Online Network
        • Linkedin For Research And Networking
        • Building An In-Person Network
        • Opening The Line Of Communication
      • Applying to Jobs
        • Applying To Jobs Online
        • Cover Letters
      • Interviewing
        • Networking Coffees vs Formal Interviews
        • The Coffee Meeting/ Informational Interview
        • Communicating With Recruiters And HR Professional
        • Research Before an Interview
        • Preparing Questions for Interviews
        • Phone And Video/Virtual Interviews
        • Cultural/HR Interview Questions
        • The Salary Question
        • Talking About Apps/Projects You Built
        • Sending Thank You's After an Interview
      • Technical Interviewing
        • Technical Interviewing Formats
        • Code Challenge Best Practices
        • Technical Interviewing Resources
      • Communication
        • Following Up
        • When You Haven't Heard From an Employer
      • Job Offers
        • Approaching Salary Negotiations
      • Staying Current in the Tech Industry
      • Module 6 Post Work
      • Interview Prep
  • projects
    • Text Classification
    • TERRA-REF
    • saildrone
  • Computer Graphics
  • AI/ML
  • 3deeplearning
    • Fast and Deep Deformation Approximations
    • Compress and Denoise MoCap with Autoencoders
    • ‘Fast and Deep Deformation Approximations’ Implementation
    • Running a NeuralNet live in Maya in a Python DG Node
    • Implement a Substance like Normal Map Generator with a Convolutional Network
    • Deploying Neural Nets to the Maya C++ API
  • Tools/Plugins
  • AR/VR
  • Game Engine
  • Rigging
    • Deformer Ideas
    • Research
    • brave rabbit
    • Useful Rigging Links
  • Maya
    • Optimizing Node Graph for Parallel Evaluation
  • Houdini
    • Stuff
    • Popular Built-in VEX Attributes (Global Variables)
Powered by GitBook
On this page
  • Why Your Pitch Matters
  • Crafting Your Own
  • Cues to Launch Your Pitch
  • Know Your Audience
  • Taking a Breath
  • Next Steps
  1. career
  2. Carrier Prep
  3. Effective Networking

30 Second Elevator Pitch

After reading through this lesson, students should be able to define what an elevator pitch is, identify the parts of their background they should include (or not include) in their own elevator pitch, and be prepared to record themselves saying their pitch in a video recording.

Why Your Pitch Matters

Throughout your job search, you’ll be prompted for your elevator pitch. It might be at a networking event where someone asks you, “What’s your story?” or in an interview that starts with, “Tell me about yourself.” Also known as a “30-second pitch,” the elevator pitch is your opportunity to tell someone who you are, pique that person’s interest in your skills and experiences, and to make a good first impression.

It would be difficult and ineffective to attempt to tell your full life story in the length of time of an elevator ride. Aim for a short summary of your career progression, leading up to and after Flatiron School, with an emphasis on your professional skills and goals.

Your elevator pitch is a foundational part of how you position yourself as a candidate for a job. Nail down this part of your preparation, because the rest will build upon it. Thinking about and saying your elevator pitch may make you uncomfortable. That’s normal—a lot of people feel nervous talking about themselves. Yes, it involves talking about and even selling yourself, but it opens new doors for you and can get a conversation going with a new contact.

Crafting Your Own

An effective pitch is concise and emphasizes your strengths.

When you’re given the opportunity to make your pitch, don’t ask, “What do you want to know?” Nothing kills a potential conversation more than you not being ready. It can also come across as defensive, which also kills a potential conversation.

As you begin drafting your elevator pitch, here are a few things to focus on:

  • Your background; including the technical aspects of your background where applicable

  • Your transition into your field of study; highlighting why you love it

  • What value you bring

  • What you're building

You’re building a story arc here. You need a narrative that a person can follow. It can start with your education and flow chronologically to present day or it can start with where you are now and what you’re working on, then go into your past a bit and connect the dots. Either way, you’re likely to wrap up with your current professional interests and where you want to take your skills next. Here’s an example (that happens to be developer focused, but the structure of which is adaptable to any field):

*“I’m a programmer and recovering attorney. I’m just about to wrap up my training at Flatiron School and I’m excited to combine my years of experience negotiating contracts and working with clients with my new expertise in Ruby on Rails and JavaScript to a new opportunity as a developer. I’m working on a small front end project for a startup that connects users to standard legal contracts that they can customize to their needs. So far, it’s been a neat combination of my skills and interests and I’d like to find similar opportunities in my next gig.” *

If you're looking for inspiration, here are a few questions to ask yourself:

  • What am I good at?

  • What problems have I solved?

  • Why do I want to be a [developer/data scientist, etc.]?

  • What was my first exposure to [code/big data, etc.]?

  • What am I passionate about?

  • What was my ‘AHA’ moment to pivot into my new field of study?

As tempting as it might be to write a script and memorize it, don’t. You want to avoid sounding too rehearsed. Draft a few key points that you always want to cover in your pitch and include them in whatever pitch you give (adapted appropriately to your audience, of course - i.e. a technical hiring manager vs. an HR representative). It won’t feel perfect every time, and that’s okay. It’s better to forget a part of your pitch than to sound like a robot.

Avoid rambling or getting too personal. Especially when someone says something as broad as, “Tell me about yourself,” it's easy to start talking about where you were born, where you went to high school, followed by some other personal story that has you babbling on for five minutes. If you’ve already thought about the relevant skills and professional experiences you want to highlight, you won’t be caught off guard by something like this and accidentally start talking about your cat.

Speak from the heart; never read straight off a screen, notes, etc. The very worst thing you can do when you meet someone for the first time is to sound robotic and impersonal. This is true, whether you are speaking face to face in person, on the phone, via video chat, or any other medium. Given that you will want to customize your pitch each and every time based on your audience and what is relevant to them in that moment so you can best engage with them (we cover this in more detail in Know Your Audience below), it is critical that you build the skills and confidence in articulating a personalized pitch in the moment, as needed.

Cues to Launch Your Pitch

No one is going to look at you and say “Okay! Now give me your elevator pitch!” Below are possible scenarios in which you’ll know to give your pitch without having to be prompted explicitly:

At a networking coffee meeting:

  • “Tell me about yourself.”

  • “So, what’s your story?”

  • “What can I do for you?”

  • “What can I do for you?”

  • “How did you get into [your field of study]?”

At a meetup/conference/networking event:

  • “What brought you here?”

  • “What do you do?”

In an interview:

  • "Tell me about yourself"

  • "Tell me how you got here?"

In a social setting:

  • “What do you do?”

Know Your Audience

Your pitch will change depending on the audience. For example, consider whom you’re speaking to and what outcome you’re looking for from the conversation. Aside from introducing yourself at a networking event or interview, you can also use your elevator pitch in emails, cover letters, blog bios, at career fairs and conferences. The bones of your elevator pitch won’t change, but it’s important to know and adapt to your audience.

Think about the length of your pitch because everyone has an agenda. An interviewer who has already committed to a conversation with you is open to a pitch longer than 30 seconds. Someone you meet at the drinks table at a meetup or at an industry conference who is in a hurry might only have 20-30 seconds before they decide if they want to invest time in talking with you further.

Here are a few questions to mull over as you prepare your elevator pitch:

  • Q: How does the size of the company change the pitch you give to an employee at that company?

A: Small companies tend to look for “scrappy”, Jack/Jane-of-all trades types so if you have additional skills to offer besides those in your program of study (like you love interfacing with clients or you can help with graphic design projects), highlight them. Small companies also have a more casual/familiar culture so you can use more informal language when you speak. Larger companies tend to be more formal and you should tailor your language accordingly.

  • Q: How does your pitch change when you’re sending a cold email versus writing an “About Me” page for your personal website/portfolio?

A: It may not be appropriate to immediately start talking about what kind of job you’re looking for in a cold email since the reader may not be prepared for it (or it could come off as “aggressive”). When contacting someone out of the blue, spend more time talking about the other person and why you’re interested in them, than you do talking about yourself. Your personal website/portfolio, on the other hand, would be the perfect place to dive into the kind of work that inspires you and all of the other talents and experience (and projects!) you bring to the table.

  • Q: How does your pitch change in a group vs. a 1:1 setting?

A: Being thoughtful about your listener or listeners is an important component of a strong elevator pitch. For example, if you’re in a large group, you may want to be mindful of how much time your pitch takes and abbreviate it, because you don’t know the agenda of the other people in the group. If you are in a group, engage others by asking questions about their backgrounds or you may naturally notice in your elevator pitch that something you’ve done ties into their experience. Remember the point of being in a group is to maintain a conversation and not rant your monologue.

  • Q: How does your pitch change if your listener is pressed for time?

A: Again, this would be an example of a time where you would need to abbreviate your pitch in order to be accommodating to your listener. Be aware of visual cues. If the person you’re talking to stops making eye contact it may mean that they aren’t interested in hearing more about you. Don’t take it personally, try asking that person about himself or herself to keep the conversation going. If that doesn’t work, move on to someone else.

Taking a Breath

A mistake a lot of people make when giving their elevator pitch is they assume they must get it out in one breath, without stopping. When people do this, it’s a lot more obvious that the person is “doing their elevator pitch” rather than just talking about themselves as one would in a normal conversation.

Remember, your elevator pitch is meant to start a conversation, so if someone asks you a question in the middle of it, welcome the interruption! Don’t try to force your full pitch on your listener if they’re already engaged and want to learn more about a specific thing you mentioned. For example, say you meet someone at a networking event who also attended a bootcamp, it’s okay to not finish your pitch and to have the conversation about your experience at Flatiron School—after all, you’ve already achieved your goal of making a meaningful connection.

To keep the conversation going, you may want to think about what questions you might have for your new contact. Whether you finish your pitch or not, these questions can help keep the conversation flowing. Here’s a tip for thinking of questions: People love to talk about themselves and to give advice. Asking someone how they got their start in the field is a great way to take the connection further.

Next Steps

PreviousEffective NetworkingNextLeveraging Your Network

Last updated 5 years ago

Check out from Career Services for additional insight into crafting your Elevator Pitch, and begin to work with your coach on the best way to tell your story!

this short video