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Post #420 1.31K
ShareChat is hiring Product Analyst Intern 🚀

Qualification : Bachelor's degree
Experience : Freshers / Experienced
Location : Bangalore

Apply link : Check out this job at ShareChat: https://www.linkedin.com/jobs/view/4197858780
Linkedin ShareChat hiring Intern- Product Analyst in Bengaluru, Karnataka, India | LinkedIn Posted 9:08:24 AM. Who are we and What do we do? ShareChat (https://sharechat.com/about) is India's largest homegrown…See this and similar jobs on LinkedIn.
Post #417 1.33K
FinBox is hiring Data Analyst 🚀

Experience : 1+ Year
Location : Gurgaon

Apply link : https://www.instahyre.com/job-364319-data-analyst-at-finbox-gurgaon/?utm_source=linkedin&utm_medium=listing&utm_campaign=linkedin_apply&utm_content=364319
Instahyre Data Analyst job at FinBox - Instahyre FinBox is looking for a Data Analyst in Gurgaon with 1-3 years of experience in Data Analysis / Business Intelligence, Matplotlib, NumPy, Python, Risk Assessment, SQL, Tableau, pandas, etc. Apply today and get your dream job at FinBox!
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Post #414 1.37K
©How fresher can get a job as a data scientist?©

Job market is highly resistant to hire data scientist as a fresher. Everyone out there asks for at least 2 years of experience, but then the question is where will we get the two years experience from?

The important thing here to build a portfolio. As you are a fresher I would assume you had learnt data science through online courses. They only teach you the basics, the analytical skills required to clean the data and apply machine learning algorithms to them comes only from practice.

Do some real-world data science projects, participate in Kaggle competition. kaggle provides data sets for practice as well. Whatever projects you do, create a GitHub repository for it. Place all your projects there so when a recruiter is looking at your profile they know you have hands-on practice and do know the basics. This will take you a long way.

All the major data science jobs for freshers will only be available through off-campus interviews.

Some companies that hires data scientists are:
Siemens
Accenture
IBM
Cerner

Creating a technical portfolio will showcase the knowledge you have already gained and that is essential while you got out there as a fresher and try to find a data scientist job.

Credits: https://t.me/datasciencefun
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Post #411 1.39K
Creating a data science portfolio is a great way to showcase your skills and experience to potential employers. Here are some steps to help you create a strong data science portfolio:

1. Choose relevant projects: Select a few data science projects that demonstrate your skills and interests. These projects can be from your previous work experience, personal projects, or online competitions.

2. Clean and organize your code: Make sure your code is well-documented, organized, and easy to understand. Use comments to explain your thought process and the steps you took in your analysis.

3. Include a variety of projects: Try to include a mix of projects that showcase different aspects of data science, such as data cleaning, exploratory data analysis, machine learning, and data visualization.

4. Create visualizations: Data visualizations can help make your portfolio more engaging and easier to understand. Use tools like Matplotlib, Seaborn, or Tableau to create visually appealing charts and graphs.

5. Write project summaries: For each project, provide a brief summary of the problem you were trying to solve, the dataset you used, the methods you applied, and the results you obtained. Include any insights or recommendations that came out of your analysis.

6. Showcase your technical skills: Highlight the programming languages, libraries, and tools you used in each project. Mention any specific techniques or algorithms you implemented.

7. Link to your code and data: Provide links to your code repositories (e.g., GitHub) and any datasets you used in your projects. This allows potential employers to review your work in more detail.

8. Keep it updated: Regularly update your portfolio with new projects and skills as you gain more experience in data science. This will show that you are actively engaged in the field and continuously improving your skills.

By following these steps, you can create a comprehensive and visually appealing data science portfolio that will impress potential employers and help you stand out in the competitive job market.
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Post #406 1.51K
Some useful telegram channels to learn data analytics & data science

Python interview books
👇👇
https://t.me/dsabooks

Data Analyst Interviews
👇👇
https://t.me/DataAnalystInterview

SQL for data analysis
👇👇
https://t.me/sqlanalyst

Data Science &  Machine Learning
👇👇
https://t.me/datasciencefun

Data Science Projects
👇👇
https://t.me/pythonspecialist

Python for data analysis
👇👇
https://t.me/pythonanalyst

Excel for data analysis
👇👇
https://t.me/excel_analyst

Power BI/ Tableau
👇👇
https://t.me/PowerBI_analyst

Data Analysis Books
👇👇
https://t.me/learndataanalysis
Post #402 1.41K
🚀 MongoDB is Hiring – Senior Business Systems Analyst

Req ID - 1263096719

Gurugram, Haryana, India 🌟


Join team at MongoDB as we redefine CRM excellence!
This role can be based in our Gurgaon office or remotely across India.
📌 What You’ll Do:
✅ Be a Salesforce expert (Sales Cloud, Forecasting, Deal Management)
✅ Analyze user journeys & optimize processes
✅ Build scalable, cross-functional solutions
✅ Collaborate with teams like Sales, Finance & more
🎯 What We’re Looking For:
💻 Expertise in Salesforce configuration (flows, automation, reports)
🔍 Strong analytical and problem-solving skills
⚡ Agile mindset with a focus on continuous improvement

📧 Interested?
https://www.mongodb.com/careers/jobs/6707614
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Post #400 1.44K
Python.pdf5.7 MB
🔰 140+ Basic to Advanced Python Tutorial Full pdf 📝

React ❤️ for more 📱
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Post #398 1.54K
We Are Hiring- Gen AI Engineer- Remote
🚀 General AI Engineer - 2+ Years Experience in AI/ML (1+ Years in Gen AI)
As a General AI Engineer, you will play a crucial role in developing, implementing, and maintaining advanced AI systems that drive innovation and solve complex problems. You'll collaborate with cross-functional teams to design and deploy AI solutions that enhance products and services, pushing the boundaries of what AI can achieve. 🌐
Key Responsibilities:
Collaborate with cross-functional teams to design and deploy AI solutions 🤝
Develop and maintain advanced AI systems 💡
Implement innovative solutions in generative AI 🤖
Skill Set:
🖥️ Expertise in Python, Data Structures, and API Calls - Strong foundation for working with generative AI models and frameworks.
🗣️ Strong Communication Skills (Documentation & Presentations) - Ability to clearly document and present complex technical concepts for both technical and non-technical audiences.
🤝 Effective Teamwork and Solo Work - Collaborate on large projects while also driving research and development independently.
🔍 Data Mining and Text Processing - Extract valuable insights from various data sources to train and improve generative models.
⚙️ Building RAG Pipelines (Highly Desired) - Experience building retrieval-augmented generation pipelines for generative AI.
💻 Machine Learning (ML), NLP, GANs, Transformers & BERT - Solid understanding of core generative AI concepts.
🛠️ Hands-on Experience with Vector Databases - Experience with Chroma DB, PineCone, Milvus, FAISS, Arango DB for data storage and retrieval.
🤝 Collaboration - Work closely with Business Analysts (BAs), Development Teams, and DevOps teams to bring AI solutions to life.
📱 Embedded Models - Familiarity with deploying generative models on resource-constrained devices (e.g., Open AI – Ada Embedding 002 model).
⚡ Experience with POC Tools (Streamlit, Gradio) - Prototype and showcase generative AI concepts quickly.
☁️ Cloud Experience (AWS Bedrock or similar) - Expertise in deploying large-scale generative AI models on cloud platforms (e.g., EC2, ECS, S3, SageMaker).
🔍 Expertise in LLMs - In-depth knowledge of a specific LLM (e.g., OpenAI, Jurassic-1 Jumbo, LLAMA, Mistral, Mixtral, Gemini Pro).
Interested?
Please share your resume to karthicc@nallas.com 📧
  • 👍 2
Post #394 1.32K
CoinDCX is hiring for Data Engineer

Experience: 1 year
Expected Salary: 20-40 LPA

Apply here: https://careers.coindcx.com/opportunities/jd?p=eyJwYWdlVHlwZSI6ImpkIiwiY3ZTb3VyY2UiOiJsaW5rZWRpbiIsInJlcUlkIjoxMDU4LCJyZXF1ZXN0ZXIiOnsiaWQiOiIiLCJjb2RlIjoiIiwibmFtZSI6IiJ9LCJwYWdlIjoiY2FyZWVycyIsImJ1ZmlsdGVyIjotMX0%3D


AssetIntel is hiring for Frontend Engineer (Remote)

Experience: 3 year's
Expected Salary: 10-30 LPA

Apply here: https://wellfound.com/jobs/3246774-frontend-engineer-remote-india


Revvity is hiring for Intern

Experience: 0 - 2 year's
Expected Stipend: 4-7 LPA

Apply here: https://jobs.revvity.com/en/job/-/-/20539/78981709968
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Post #393 1.28K
Let’s go back to the basics...!

Here’s what you do to become a Data Analyst

- Learn SQL (best skill to have)
- Learn Excel (hidden requirement)
- Learn a BI tool (for nice portfolio projects)

Don’t stop there you still have work to do

- Create a portfolio
- Learn how to create an appealing resume
- Learn how to answer interview questions (STAR method)

After this, my favorite, networking

- Comment on posts
- Start posting yourself
- Reach out to all the recruiters

It can take you anywhere from a couple of months to a year!

It all depends on how much time you can dedicate each day!

But the longer you wait, the longer it will take!

Get after it...!
  • 👍 2
Post #384 1.47K
1. What are the uses of using RNN in NLP?

The RNN is a stateful neural network, which means that it not only retains information from the previous layer but also from the previous pass. Thus, this neuron is said to have connections between passes, and through time.
For the RNN the order of the input matters due to being stateful. The same words with different orders will yield different outputs.
RNN can be used for unsegmented, connected applications such as handwriting recognition or speech recognition.

2. How to remove values to a python array?

Ans: Array elements can be removed using pop() or remove() method. The difference between these two functions is that the former returns the deleted value whereas the latter does not.

3. What are the advantages and disadvantages of views in the database?

Answer: Advantages of Views:
As there is no physical location where the data in the view is stored, it generates output without wasting resources.
Data access is restricted as it does not allow commands like insertion, updation, and deletion.
Disadvantages of Views:
The view becomes irrelevant if we drop a table related to that view.
Much memory space is occupied when the view is created for large tables.

4. Describe the Difference Between Window Functions and Aggregate Functions in SQL.

The main difference between window functions and aggregate functions is that aggregate functions group multiple rows into a single result row; all the individual rows in the group are collapsed and their individual data is not shown. On the other hand, window functions produce a result for each individual row. This result is usually shown as a new column value in every row within the window.

5. What is Ribbon in Excel and where does it appear?

The Ribbon is basically your key interface with Excel and it appears at the top of the Excel window. It allows users to access many of the most important commands directly. It consists of many tabs such as File, Home, View, Insert, etc. You can also customize the ribbon to suit your preferences. To customize the Ribbon, right-click on it and select the “Customize the Ribbon” option.
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