Spam Comment Remover Yelp in Canada @Privatejobsmumbai(Applied Scientist)

Company Name: Yelp

Job Name: Applied Scientist

Salary: Can$ 20 – Can$ 30/Hour

Qualification: Bachelor’s Degree

Location: Canada

Spam Comment Remover Yelp in Canada

Full Job Description

The foundation of the Yelp engineering culture is laid out by our values as a cohesive team that values individual authenticity and encourages creative problem-solving. Within the first week, every new engineer releases a working code, and we strive to maximize individual impact with the help of managers, mentors, and teams. Everything we do ultimately revolves around assisting our users, growing as engineers, and having fun as a team.
The goal of Yelp’s Ads team is to create a valuable, healthy marketplace between customers and a business by working on complex, multidisciplinary problems at scale spanning machine learning, data structures and algorithms, optimization, statistics, and distributed systems.
As an applied scientist in the Ads division, you will be a member of a group that focuses on control systems, experimentation, pricing, and auction bidding strategies. Applied scientists transform these realizations into statistical or predictive models that are used in production after conducting exploratory research and analysis. Making sense of the data, carefully considering the system design, and identifying different network interactions all require a lot of work, but the benefits to Yelp’s operations are enormous.
This opportunity is completely remote, so you are not required to be in any particular region of Canada to take part. You can apply if you’re a Canadian citizen. We welcome your application even if you don’t feel that you completely meet the requirements listed in this job posting. At Yelp, we seek out exceptional individuals rather than just those who fit the bill.

What you will do is:

Establishing and accepting responsibility for challenging issues, creating testable hypotheses, and producing significant business impact.
Organize the development of causal and predictive models or the planning and evaluation of experiments to verify your hypotheses.
Modify production procedures with the help of engineering and product, and provide information to other teams.
Both technical and non-technical audiences should hear about your findings.
The team can stay current on new developments in ML and statistics by reading papers, attending conferences, and taking part in local events.
Model pipelines in Python services should be automated and productized.

To succeed, you must:

A bachelor’s degree or equivalent work experience counts as required qualifications.
a degree in a quantitative field, such as physics, applied math, computer science, statistics, economics, etc.
It would be advantageous to know statistical software and packages (such as R, Python’s pandas, Statsmodels, and Sklearn). ).
understanding of causal inference, predictive modeling, or machine learning.
You don’t need to be an expert, but some experience is helpful, and we’ll expect you to learn as you go. A passion for writing elegant code.
demonstrated success in applied research, a desire to discover potential solutions for novel problems, and the tenacity to see your ideas through to completion.
a desire to become an expert in a particular product or sector and to understand how to connect analytical tasks like abstract modeling to real-world applications.
working easily in a Unix environment.

You will get the following.