20 things experienced Data Scientists know which beginner Data Scientists do not knowSoftware TrainingUpdated on May 9, 2019 View more like this | Visit CALIFORNIA, PA | Contact IQ Online Training |
1. Writing code to write code i.e. automating tasks ;)
2. Training others to make them tech-savvy
3. Hiring the right candidates, Managing candidates, and managers who report to you
4. Be an advisor to managers or higher officials
5. Outsourcing tasks to junior members or to consultants whenever required.
6. Knowledge of popular tools, identifying the right tools, assessing the pros & cons of different software and platforms when doing a large-scale project
7. Choosing the right algorithms & statistical techniques while in a project and using those techniques as per the requirement for better performance.
8. Identifying various internal or external data sources, using important data from all those while cleaning data redundancies and other data issues. i.e. not trusting single data.
9. Good understanding of the project or business – identifying the best features; combining them to form other better predictors
10. Good understanding of the project requirements; translating all the requests, concerns, questions, ideas etc. from the client into a better data science output
11. Being able to predict the hurdles that hinder a complex project from developing and assess the time frame required for the completion of the project.
12. Evaluating the ROI of a company brought by us, we can be in a position to explain the positive ROI or negative ROI. If we bring negative ROI, we can direct them a path to correct it with all the knowledge we have.
13. Being able to create a new project or manage a project from start to finish
14. Be in a position to deliver the output in a timely fashion and work consistently despite other setbacks. Have a clear knowledge of the factors that create value for the company.
15. We know what we do not know or what to learn or what to outsource
16. Being able to predict the fake news that is roaming around the internet or on social media and take only original content
17. Can make sure a project that started well will end well within a specified time by helping with maintenance and making many recommendations about the implementations
18. Have a good understanding of the business we are in and a good vision even if no one says.
19. Have a gut feeling in whatever we do and trust our intuition in doing so.
20. Ease of documenting, prioritizing everything. Good communication with stakeholders and good planning
2. Training others to make them tech-savvy
3. Hiring the right candidates, Managing candidates, and managers who report to you
4. Be an advisor to managers or higher officials
5. Outsourcing tasks to junior members or to consultants whenever required.
6. Knowledge of popular tools, identifying the right tools, assessing the pros & cons of different software and platforms when doing a large-scale project
7. Choosing the right algorithms & statistical techniques while in a project and using those techniques as per the requirement for better performance.
8. Identifying various internal or external data sources, using important data from all those while cleaning data redundancies and other data issues. i.e. not trusting single data.
9. Good understanding of the project or business – identifying the best features; combining them to form other better predictors
10. Good understanding of the project requirements; translating all the requests, concerns, questions, ideas etc. from the client into a better data science output
11. Being able to predict the hurdles that hinder a complex project from developing and assess the time frame required for the completion of the project.
12. Evaluating the ROI of a company brought by us, we can be in a position to explain the positive ROI or negative ROI. If we bring negative ROI, we can direct them a path to correct it with all the knowledge we have.
13. Being able to create a new project or manage a project from start to finish
14. Be in a position to deliver the output in a timely fashion and work consistently despite other setbacks. Have a clear knowledge of the factors that create value for the company.
15. We know what we do not know or what to learn or what to outsource
16. Being able to predict the fake news that is roaming around the internet or on social media and take only original content
17. Can make sure a project that started well will end well within a specified time by helping with maintenance and making many recommendations about the implementations
18. Have a good understanding of the business we are in and a good vision even if no one says.
19. Have a gut feeling in whatever we do and trust our intuition in doing so.
20. Ease of documenting, prioritizing everything. Good communication with stakeholders and good planning
