LTIMindtree hiring Data Analyst

https://in.linkedin.com/jobs/view/data-analyst-at-ltimindtree-4207304045

Google hiring Senior Data Scientist

Location: Bengaluru

Apply link: https://careers.google.com/jobs/results/140500223645360838-senior-data-scientist/?src=Online/LinkedIn/linkedin_us&utm_source=linkedin&utm_medium=jobposting&utm_campaign=contract

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IBM hiring Data Scientist

Location : Pune

Apply link: https://www.linkedin.com/jobs/view/4207399869

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Microsoft hiring Data Scientist

Apply link: https://jobs.careers.microsoft.com/global/en/job/1816527

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Python project-based interview questions for a data analyst role, along with tips and sample answers [Part-1]

1. Data Cleaning and Preprocessing
- Question: Can you walk me through the data cleaning process you followed in a Python-based project?
- Answer: In my project, I used Pandas for data manipulation. First, I handled missing values by imputing them with the median for numerical columns and the most frequent value for categorical columns using fillna(). I also removed outliers by setting a threshold based on the interquartile range (IQR). Additionally, I standardized numerical columns using StandardScaler from Scikit-learn and performed one-hot encoding for categorical variables using Pandas' get_dummies() function.
- Tip: Mention specific functions you used, like dropna(), fillna(), apply(), or replace(), and explain your rationale for selecting each method.

2. Exploratory Data Analysis (EDA)
- Question: How did you perform EDA in a Python project? What tools did you use?
- Answer: I used Pandas for data exploration, generating summary statistics with describe() and checking for correlations with corr(). For visualization, I used Matplotlib and Seaborn to create histograms, scatter plots, and box plots. For instance, I used sns.pairplot() to visually assess relationships between numerical features, which helped me detect potential multicollinearity. Additionally, I applied pivot tables to analyze key metrics by different categorical variables.
- Tip: Focus on how you used visualization tools like Matplotlib, Seaborn, or Plotly, and mention any specific insights you gained from EDA (e.g., data distributions, relationships, outliers).

3. Pandas Operations
- Question: Can you explain a situation where you had to manipulate a large dataset in Python using Pandas?
- Answer: In a project, I worked with a dataset containing over a million rows. I optimized my operations by using vectorized operations instead of Python loops. For example, I used apply() with a lambda function to transform a column, and groupby() to aggregate data by multiple dimensions efficiently. I also leveraged merge() to join datasets on common keys.
- Tip: Emphasize your understanding of efficient data manipulation with Pandas, mentioning functions like groupby(), merge(), concat(), or pivot().

4. Data Visualization
- Question: How do you create visualizations in Python to communicate insights from data?
- Answer: I primarily use Matplotlib and Seaborn for static plots and Plotly for interactive dashboards. For example, in one project, I used sns.heatmap() to visualize the correlation matrix and sns.barplot() for comparing categorical data. For time-series data, I used Matplotlib to create line plots that displayed trends over time. When presenting the results, I tailored visualizations to the audience, ensuring clarity and simplicity.
- Tip: Mention the specific plots you created and how you customized them (e.g., adding labels, titles, adjusting axis scales). Highlight the importance of clear communication through visualization.

Like this post if you want next part of this interview series 👍❤️

𝗗𝗿𝗲𝗮𝗺 𝗝𝗼𝗯 𝗮𝘁 𝗚𝗼𝗼𝗴𝗹𝗲? 𝗧𝗵𝗲𝘀𝗲 𝟰 𝗙𝗥𝗘𝗘 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗪𝗶𝗹𝗹 𝗛𝗲𝗹𝗽 𝗬𝗼𝘂 𝗚𝗲𝘁 𝗧𝗵𝗲𝗿𝗲😍

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Uber hiring Data Scientist

Location: Hyderabad

Apply link: https://www.uber.com/global/en/careers/list/140262/

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Micro1 hiring Machine Learning Engineer

Apply link: https://jobs.micro1.ai/post/4e8ab90a-fa1e-464b-bc64-fe7e980be1d6/

Required Skills and Qualifications

Proficiency in Python and its libraries for machine learning.
Strong understanding and practical experience with machine learning algorithms and AI principles.
Proven experience with MongoDB for data management and integration.
Excellent written and verbal communication skills, demonstrating the ability to convey technical concepts clearly.
Experience in the complete development and deployment lifecycle of an ML/AI project.
Capacity to work independently and collaboratively in a remote environment.

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Wipro is hiring!
Position: Data Scientist
Qualification: Bachelor’s/ Master’s Degree
Salary: 6 - 13 LPA (Expected)
Experience: Freshers/ Experienced
Location: Bengaluru, India

📌Apply Now: https://careers.wipro.com/job/Bengaluru-Data-Scientist-L3-560035/1156126755/

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HDFC Hiring Data Scientist

Apply link: https://www.linkedin.com/jobs/view/4211300029

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American Express hiring Data Scientist

Location: Gurgaon

Apply link: https://aexp.eightfold.ai/careers/job/26865284?hl=en&utm_source=linkedin&domain=aexp.com

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Colgate hiring Data Scientist

Apply link: https://jobs.colgate.com/job/Mumbai-Data-Scientist-MH/1273416700

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