As a data scientist fresher, you’re embarking on an exciting career path that involves extracting valuable insights from data. Here are some essential steps and tips to get started in your journey as a data scientist:

1. Learn the Fundamentals: Start by building a strong foundation in mathematics, statistics, and programming. Knowledge of Python is particularly valuable as it’s widely used in the data science field.

2. Acquire Data Skills: Data is the heart of data science. Learn how to collect, clean, and preprocess data. Familiarize yourself with libraries like Pandas for data manipulation.

3. Master Machine Learning: Understand the principles of machine learning. Learn about various algorithms, their pros and cons, and when to use them. Scikit-Learn is a popular Python library for this purpose.

4. Data Visualization: Learn how to create meaningful visualizations using libraries like Matplotlib and Seaborn. Effective data visualization can help in understanding and communicating insights from data.

5. Exploratory Data Analysis (EDA): Practice EDA to gain insights from data before diving into modeling. It involves summary statistics, data visualization, and identifying patterns.

6. Projects and Portfolios: Work on personal projects or participate in Kaggle competitions to apply your skills. Building a portfolio of projects is crucial to demonstrate your abilities to potential employers.

7. Networking: Join data science forums, LinkedIn groups, and attend data science meetups or conferences if possible. Networking can help you learn from experienced professionals and discover job opportunities.
   

8. Online Communities: Engage with online communities like Stack Overflow and GitHub to share your knowledge, ask questions, and collaborate on open-source projects.

9. Build a Strong Resume: Craft a data science-specific resume highlighting your skills, projects, and any relevant experience, even if it’s from internships or personal projects.

10. Apply for Internships: Consider applying for internships or entry-level positions to gain practical experience. Many companies offer internship programs for data science roles.

11. Stay Updated: The field of data science is constantly evolving. Stay up-to-date with the latest trends, research papers, and technologies in the data science and machine learning domain.

12. Soft Skills: Don’t forget about soft skills like communication, problem-solving, and teamwork. These skills are important in any data science role.

13. Prepare for Interviews: Brush up on technical and behavioral interview questions. Be ready to discuss your projects and demonstrate your problem-solving abilities during interviews.

14. Be Persistent: Landing your first job as a data scientist may take time and multiple applications. Don’t get discouraged; keep learning and improving your skills.