Where can you find qualified {role_name}?

What are the best practices for headhunting {role_name}?

How to shortlist candidates?

Once you have started to get applications from applicants, a thorough screening process and shortlisting of prospects will help you make the most of your time spent with the most qualified ones. 

Automated shortlisting tools :

Automated screening quickly filters out unqualified candidates, saving time for manual review. This allows the manual process to focus on the most promising candidates, ensuring the best ones are considered for further evaluation.

Screening questions to auto-shortlist based on predefined criteria

like qualifications, location, experience, and skills. Either use job board or use an ATS such as whitecarrot. Here are some questions for {role_name}

• Experience with AI and Machine Learning:
  • Question: "How many years of experience do you have with AI and Machine Learning technologies?"
  • Auto-Reject Criteria: Less than 2 years of experience.
• Experience in Related Technology:
  • Question: "How many years of experience do you have in programming with Python or R?"
  • Auto-Reject Criteria: Less than 3 years of programming experience.
• Location Flexibility:
  • Question: "Are you located within [specified location] or willing to work remotely?"
  • Auto-Reject Criteria: Not located within the required area and unwilling to work remotely.

Skill based question to auto shortlist candidate

Analyze the skill test data to automatically shortlist top-performing applicants. (recommended screening test time - 15 minutes). Here are some skill test questions for {role_name}

Machine Learning

Assessing the candidate's knowledge of machine learning principles.

• Question: "Which algorithm is typically used for classification problems?"
  • A) Linear Regression
  • B) Decision Trees
  • C) K-Means Clustering
  • D) Apriori
  • Correct Answer: B) Decision Trees
• Question: "What is overfitting in machine learning?"
  • A) When the model performs well on training data but poorly on new data
  • B) When the model performs poorly on training data but well on new data
  • C) When the model performs well on both training and new data
  • D) When the model cannot make any predictions
  • Correct Answer: A) When the model performs well on training data but poorly on new data
• Question: "Which of the following is a technique to prevent overfitting?"
  • A) Increasing the size of the training dataset
  • B) Reducing the size of the training dataset
  • C) Decreasing the number of features
  • D) Using a less complex model
  • Correct Answer: A) Increasing the size of the training dataset

Deep Learning

Evaluating the candidate’s understanding of deep learning concepts.

• Question: "What is a convolutional neural network (CNN) primarily used for?"
  • A) Natural language processing
  • B) Image recognition
  • C) Time series forecasting
  • D) Reinforcement learning
  • Correct Answer: B) Image recognition
• Question: "What does backpropagation in a neural network involve?"
  • A) Forward passing the input data
  • B) Adjusting the weights based on the error gradient
  • C) Initializing weights and biases
  • D) Collecting data for the network
  • Correct Answer: B) Adjusting the weights based on the error gradient
• Question: "Which activation function is most commonly used in deep learning models?"
  • A) Sigmoid
  • B) Tanh
  • C) ReLU (Rectified Linear Unit)
  • D) Softmax
  • Correct Answer: C) ReLU (Rectified Linear Unit)

Data Analysis

Testing the candidate’s data analysis capabilities.

• Question: "Which method is used to identify patterns in a dataset?"
  • A) Normalization
  • B) Clustering
  • C) Sorting
  • D) Filtering
  • Correct Answer: B) Clustering
• Question: "What is the purpose of cross-validation in model evaluation?"
  • A) To split the dataset into training and test sets
  • B) To assess how the model generalizes to an independent dataset
  • C) To optimize hyperparameters
  • D) To reduce overfitting
  • Correct Answer: B) To assess how the model generalizes to an independent dataset
• Question: "Which Python library is most commonly used for data manipulation?"
  • A) NumPy
  • B) Pandas
  • C) SciPy
  • D) Matplotlib
  • Correct Answer: B) Pandas

Note - Auto reject candidates if scores less than 70% in this section

One way video interview

Use tools like hirevue, whitecarrot.io to ask candidates pre-recorded questions about their experience and skills.

Use sample question given in scorecard.

Collect other information 

Collect data from shortlisted candidates, such as salary expectations and visa status.

Manual candidate profile shortlisting:

Thoroughly review the CVs of the top scoring candidates from the automated process

Look for evidence of the required skills, experience, and achievements

Review the candidate’s portfolio or GitHub repositories to see examples of their work.