Credence Resource Management Data Analyst Interview Questions and Answers

Q1. Walk through your project?
Ans. 
Developed a predictive model to forecast sales based on historical data
• Collected and cleaned historical sales data

• Performed exploratory data analysis to identify trends and patterns

• Built and trained a machine learning model using regression techniques

• Evaluated model performance using metrics like RMSE and MAE
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Q2. Behavioral questions?
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Q1. Questions based on Advanced Excel like Vlookup, Index match, sumifs, pivot tables
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Q2. Behavioral questions
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Q1. Salary negotiation
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Q1. What is the name of the company you have worked for, and what is your past experience?
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Medical knowledge based questions

Q1. General medical questions
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Q2. Antidiabetics , gerd, antihypertension,gout,bones,fracture
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Q1. Introducation salary expectation skills personality
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Q1. Introduction, Journey, questions from CV
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Quantitative and Non-verbal Aptitude

HTML, CSS, JavaScript

Q1. Top 2nd salary in the IT department
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Q2. Questions related to Window Functions.
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Q1. Salary structure and negotiation
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Self details

Java, python, r, powerbi

About powerbi, they have conducted.....

Q1. What is Logistic regression
Ans. 
Logistic regression is a statistical method used to analyze and model the relationship between a binary dependent variable and one or more independent variables.
• It is a type of regression analysis used for predicting the probability of a categorical dependent variable

• It is commonly used in marketing, finance, and healthcare industries

• It uses a sigmoid function to map any real-valued number to a value between 0 and 1

• Exa...read more
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Q2. What are Random Forests
Ans. 
Random Forests is an ensemble learning method for classification, regression and other tasks.
• Random Forests is a machine learning algorithm that builds multiple decision trees and combines their outputs.

• It is an ensemble learning method that uses bagging and feature randomness to improve the accuracy and prevent overfitting.

• Random Forests can be used for classification, regression, feature selection, and outlier detect...read more
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Q1. What is Natural Language Processing
Ans. 
Natural Language Processing is a field of study that focuses on making computers understand human language.
• It involves using algorithms and statistical models to analyze and interpret human language.

• NLP is used in various applications such as chatbots, sentiment analysis, and language translation.

• Examples of NLP tools include NLTK, spaCy, and Stanford CoreNLP.
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Q2. What is BERT & Transformers
Ans. 
BERT & Transformers are natural language processing models used for tasks such as sentiment analysis, question answering, and language translation.
• BERT stands for Bidirectional Encoder Representations from Transformers and is a pre-trained language model developed by Google.

• Transformers are a type of neural network architecture that can process sequential data, such as text, by attending to different parts of the input...read more
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Q3. What are common OCR techniques
Ans. 
OCR techniques include preprocessing, segmentation, recognition, and postprocessing.
• Preprocessing involves enhancing the image quality and removing noise.

• Segmentation is the process of identifying individual characters or words in the image.

• Recognition involves using machine learning algorithms to recognize the characters or words.

• Postprocessing involves correcting errors and improving the accuracy of the recognized te...read more
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