ML Data Scientist

Job Title: ML Data Scientist

Location: Any Infosys Hub office (Hybrid)

Duration: Long term contract  

Visa: USC/ Only

Domain Oil and Gas

Job Description:

1. Candidate needs to have in-depth knowledge of Python modular code and how the  algorithm works

2. Candidate needs to exhibit trying to understand mathematical intuition behind the  algorithm

3. Candidate ideally good to have AWS exposure or stack where they have worked for this classical ML in that environment. (Not mandatory but it will be easy to pick up  and good to have)

4. Good in Python Coding and is mandatory(Should know Modular coding)

5. Good understanding of core traditional machine modeling models

6. Very traditional classical model is essential

7. Good abstract thinking of the ML model and deep ML experience is required.

8. Core classical machine learning models need to be built, example is, if we build  Random Forest model - how does it work?, challenge is also to give a business friendly answer

9. They are looking for people who have practically done these models before

10. Candidate needs to be well versed to understand what it takes to have a machine  learning model built and deployed in production, As long as they have done in some  platform if they can demonstrate will be great.

11. From operations side it is no longer a requirement and need to know AWS as a hard  requirement but good to have.

12. Also building models and help improve performance of model is needed

13. There is no compromise on good communication skills and should be able to elicit  and requirements.

Mandatory skills*           

From operations side it is no longer a requirement and need to know AWS as a hard requirement but good to have.  Also building models and help improve performance of model is needed .There is no compromise on good communication skills and should be able to elicit and requirements.

Desired skills*   

From operations side it is no longer a requirement and need to know AWS as a hard requirement but good to have.  Also building models and help improve performance of model is needed. There is no compromise on good communication skills and should be able to elicit and requirements.