Elementals.ai jobs - Data Science
Data Science
Fresher
Salary not disclosed
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Job Description
Selected intern's day-to-day responsibilities include:
1. Work on sentiment analysis, NER, PoS tagging, and other NLP related tasks
2. Work on transformer and BERT based DL models
3. Work on recommender systems
4. Work on forecasting & analytics
5. Deploy ML models and create APIs
Note: It is not required to be aware of all the concepts. However, we look for bright students who showcase the ability to quickly learn and adapt. One of our most important criteria is that the student is independent whilst being given a task.
Only those candidates can apply who:
1. are available for full time (in-office) internship
2. can start the internship between 27th Dec'20 and 31st Jan'21
3. are available for duration of 6 months
4. have relevant skills and interests
* Women wanting to start/restart their career can also apply.
1. Must be a final year student or recent graduates who are able to spend at least 6 months in the internship
2. Students who have strong programming skills and confidence in algorithms & data structures
3. Must have a basic understanding of ML concepts like linear & logistic regression, SVMs, and neural network architectures
4. Must have worked on any simple data science or NLP based project
Job offer: On successful conversion to a permanent employee, the candidate can expect a salary of Rs. 5 to 10 Lac/annum
This is a performance-based internship. In addition to the minimum assured stipend, candidates will be paid an incentive of Rs. 10000 based on their performance.
The interview process:
1. A simple algorithmic challenge to solve (helps us understand your ability to code)
2. A simple data science challenge to evaluate your DS skills
3. A final interview where you get to tell us about yourself
Perks & stipend:
1. A good stipend of Rs. 20,000 per month along with allowance to work in a great workspace worth Rs. 6,000 per month
2. Includes perks like free snacks and beverages
3. Great eco-system and work culture
4. Initial onboarding at the office (work from home once acclimatized!)
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