Data & Machine Learning Careers

 Referred Link - https://www.linkedin.com/posts/mr-deepak-bhardwaj_dataops-mlops-careerindata-activity-7217884033484038144-YPw4

Are you considering a career in Data or Machine Learning (ML)? Are you confused with various data roles and what they do?

Here’s a detailed breakdown of critical roles and their associated responsibilities:


🔘 Data Engineer: Tailored for Data Enthusiasts

1. Data Ingestion: Acquire proficiency in data handling techniques.
2. Data Validation: Master the art of data quality assurance.
3. Data Cleansing: Learn advanced data cleaning methodologies.
4. Data Standardisation: Grasp the principles of data formatting.
5. Data Curation: Efficiently organise and manage datasets.

🔘 Data Scientist: Suited for Analytical Minds

6. Feature Extraction: Hone your skills in identifying data patterns.
7. Feature Selection: Master techniques for efficient feature selection.
8. Model Exploration: Dive into the realm of model selection methodologies.

🔘 Data Scientist & ML Engineer: Designed for Coding Enthusiasts

9. Coding Proficiency: Develop robust programming skills.
10. Model Training: Understand the intricacies of model training.
11. Model Validation: Explore various model validation techniques.
12. Model Evaluation: Master the art of evaluating model performance.
13. Model Refinement: Refine and improve candidate models.
14. Model Selection: Learn to choose the most suitable model for a given task.

🔘 ML Engineer: Tailored for Deployment Enthusiasts

15. Model Packaging: Acquire knowledge of essential packaging techniques.
16. Model Registration: Master the process of model tracking and registration.
17. Model Containerisation: Understand the principles of containerisation.
18. Model Deployment: Explore strategies for effective model deployment.

These roles encompass diverse facets of Data and ML, catering to various interests and skill sets. Delve into these domains, identify your passions, and customise your learning journey accordingly.

Tags:

#DataOps hashtag#MLOps hashtag#CareerInData hashtag#MachineLearning hashtag#DataScience #AI#ML hashtag#BestPractices