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
  • Self-Confidence vs. Self-Compassion
  • What Should You Do With All of This Confidence?
  • Resources
  1. career
  2. Carrier Prep
  3. The Job Search

Confidence

Searching for a new job and the related networking/interviewing can require a giant step out of your normal comfort zone. This takes confidence — confidence in your skills, in your communication, and in yourself. Easier said than done, right? In this section, we’ll take a look at the challenges of showing up with confidence and explore some strategies to boost and maintain your confidence whenever you are not quite feeling it.

Self-Confidence vs. Self-Compassion

Let’s start with the difference between confidence (or self-esteem) and self-compassion.

The trouble with self-confidence is that it is often contingent on success. In short, we judge ourselves positively when we do well. But the minute we fail or make a mistake, our confidence can fly out the window and we judge ourselves negatively.

Self-confidence tends to be fueled by comparison and whether we are doing “better” or “worse” than others. Basically, if I have high self-confidence I have to feel special and above average. Mathematically, everyone can’t be above average at the same time; this desire to be better than others is based on a logical impossibility, which is a simple reason why comparing yourself to others isn’t productive.

Self-compassion on the other hand is not earned by successes or contingent on doing well, or even comparative in nature. It’s simply about doing your best and treating one’s self kindly, like you would treat a good friend — with warmth and understanding. When we make a mistake or we fail, we may lose our self-confidence. But that is where self-compassion steps in. Self-compassion recognizes that it’s natural and normal to make mistakes, and that we’re worthy of kindness even though we may not have performed as well as we wanted to, or mis-stepped somewhere along the way. When we're kind to ourselves, we're able to see the ways in which we can grow and what we can take away from these experiences. It's not about being better than other people. It's about being better than the current version of one’s self.

The secret to increasing your confidence? Stop convincing yourself that you’re awesome and confident. Instead, forgive yourself when you’re not. Focus on learning, and think of any mistakes as things you can learn from with self-compassion in that ability to learn. Your self-compassion will shine as outward confidence because you are simply being you to the best of your ability and being kind to yourself in the process.

What Should You Do With All of This Confidence?

Roll with Rejection

There will always be other talented job seekers applying for the same companies, and chances are you will hear some form of “no” at different points in your job search. This is a normal and inescapable part of every job search, and is the perfect opportunity to practice self-compassion. Once you have treated yourself kindly, you can look at the experience in a different light. When you're not being so hard on yourself, it’s easier to assess what you learned from the experience and move on. You’ll need to have thick skin. If one door closes, use this as a prompt to reflect on what you learned and then seek out another door to open in its place.

Be Curious

Networking and cold email outreach can feel awkward and intimidating at times. If this is you, you are not alone! A highly effective way to connect with others and develop relationships is to use your curiosity as a guide. With self-compassion, you're not thinking that you're awesome and know everything. Instead, you're giving yourself the permission to put your best self forward and learn and ask real, interesting questions that you’d like to know the answers to. What do you actually want to know about the person? What makes you curious about their work or background? The more truly curious you are, the more authentic the interaction will be - and likely the more comfortable and engaging.

Know That You're Not a Burden

Don’t be shy about reaching out or assume others are too busy or don’t want to talk with you. Everyone who works at a company joined that company at some point in time and has gone through a similar process: of getting to know the company, interviewing, and accepting a position. In short, all professionals at one point or another have been a job seeker and know what it’s like to be in your shoes. Yes, many people are busy - but many people will also happily connect with you to offer their help or advice. You are not a burden and it’s up to you to take initiative to reach out.

Take It One Step at a Time

Being self-compassionate means that you're taking things one step at a time and that you don't need to know all the answers at the outset. Networking and interviewing can have ambiguous moments. For example, a potential employer may ask to schedule an introductory call but does not provide much detail beyond that. It’s key to take each interaction one step at a time and not allow yourself to get too far ahead. What is the immediate next step, and how can you best prepare? (For example, a well-written email response inclusive of a couple of available windows of time to connect, not assuming the employer isn’t interested just because his email wasn’t detailed enough.)

Ask thoughtful questions during each interaction to help bring you clarity where possible. (e.g. Could you give me a sense of what the schedule might look like for Friday’s interview?, Could you share with me your general timeline for bringing on a new programmer?) It’s often tempting to jump ahead, but resist!

Resources

PreviousYour Job Search MindsetNextJob Search Action Plan

Last updated 5 years ago

Building Confidence and Self-Esteem
10 Ways to Build Confidence
Job Search Confidence