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NOC code for analytics consultant role

bonkers9590

Newbie
Feb 2, 2020
2
0
Hello,

I would like to know the NOC code for my role below. I am confused between 2161 and 2172.

1. Using strong programming skills in Python, R, SQL, SAS to solve business problems of client and providing actionable insights

2. Using machine learning and statistical techniques like Random Forest, Regression and Neural Networks for model development

3. Lead client meetings, gather business requirements from stakeholders and ideate project approaches for efficient execution of projects

4. Working with clients to help execute their analytical projects (pilot projects, marketing campaigns) by employing advanced statistics and latest technology

5. Analyzing data present in client data-mart and performing exploratory data analyses, running descriptive statistics using analytical tools, and providing detailed insights to client to support business decisions

6. Using Tableau, Power-point and other similar visualization tools to generate reports and effectively conveying the business insights to stakeholders
 

Aryabhatt

Full Member
Dec 12, 2018
27
5
Unless you have a degree in Stats, go for 2172. It relates more to your profile. 2172 has “data scientist” as one of the job titles which was included recently in 2018.
 
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bonkers9590

Newbie
Feb 2, 2020
2
0
Unless you have a degree in Stats, go for 2172. It relates more to your profile. 2172 has “data scientist” as one of the job titles which was included recently in 2018.
Thanks! I have a degree in Analytics but not really statistics. Is there any other Job code which suits me better than 2172 you think?
 

gurubux

Newbie
Oct 30, 2019
8
0
What did you choose finally and what was the result? Did you get through. I am also very confused between 2161 and 2172.
Same query as @vmanojk123 What did you finally decide ?
Kindly suggest in my scenario as well @bonkers9590

Is 2172 or 2173 the right NOC? Data Analyst/Data Scientist/Machine Learning Developer
My job profile is to handle complete Machine learning pipeline from data cleaning, preprocessing, feature engineering, train machine learning models and predicting, also evaluating the models, deploying the model on production and more.
Tech stack involves Python coding and ML related libraries (numpy, pandas, Tensorflow and pytorch). Also cloud related technologies(AWS services (EC2, S3, RDS, ECS, Lambda)), Logging tools like Kibana and Grafana. Docker for deployment. Django, Flask, FastAPI etc Frameworks (RESTful APIs)
Kindly suggest.