We invite applications from students and working professionals with an exceptional academic record and/or a distinguished work or research experience in STEM.
DSLP applications will open soon.
Univ.AI’s consulting arm is hiring STEM students and working professionals with a robust academic or research background. On being selected, you will train for the job with professors from Harvard & UCLA on a 100% scholarship, and then begin your career as a top Data Scientist.
You must have a STEM background. Final year students, recent graduates, and working professional with less than 5 years of work experience are eligible. If you meet the criteria, we would like to consider you for one of the country’s top upcoming Data Science & AI positions.
Selected candidates receive a job offer from Univ.AI or a partner company with compensation ranging from INR 15 to 35 lacs per year*
Candidates pursue our Master ML & AI program with professors from Harvard & UCLA on a 100% scholarship.
Upon successful completion, you are assigned to client projects in Artificial Intelligence and Machine Learning.
Your application consists of a detailed questionnaire and an application test. If your score is past the cut-off, we invite you to begin training with us. After completing the first course (in about 6 weeks), your performance will be evaluated.
Selected candidates will be made DSLP job offers with compensations ranging from ₹15 to 35 lacs per year.
Once you are accepted as a DSLP fellow, we will enrol you for our 43-week part-time Master ML & AI program on a full scholarship. This means, you can continue in your current capacity as a student or working professional until you complete the fellowship. You will learn LIVE from Harvard and UCLA professors through a set of hands-on courses and train to be production ready.
You join Univ.AI’s marquee team of Data Science and AI consultants and immediately begin work on state-of-the-art machine learning projects world-wide. These projects span a diverse set of industries and applications.
Understanding contract ontology and structure to automatically classify and execute contracts, as well as to author new contracts.
Client is one of the world’s leading players in contract management.
Project involves using auto-encoders on patient data to characterise patients by disease and lifecycle.
Client is a health-care giant based in the eastern coast of the United States.
Using encoder-decoder models to learn water pressure and saturation fields in oilfields to determine exploration strategy.
Client is a US oil and gas major.
This program is designed for high-achievers with demonstrated potential. Applicants should have a superior track record as a student and if you have already graduated, then you have gone on to demonstrate high-competence and exceptional performance at your workplace.
Complete the application test
Begin training with us. Your performance will be evaluated.
Selected candidates will receive offer letters.
If you are selected as a candidate under the Data Science Leaders Program, then you will be called a DSLP fellow. In order to maintain your fellowship status, you agree to meet the following academic standards.
If you fail to fulfil these conditions, you will be deemed to have a program incomplete and will not be elligible to start your job. Candidates with legitimate reasons for their inability to mantain program status will be considered on a case by case basis. You will not owe us any tuition fee unless you choose to drop out of the program.
If you wish to work with another employer post the program, you may do so. But in this case, you will owe us an up-front amount of INR 1,00,000 followed by monthly instalments equivalent to 17% of your monthly CTC or INR 20,000 - whichever is higher - for a period of 24 months (i.e. 24 such instalments) towards the tuition fee of the program.
You will work for Univ.AI’s consulting arm as a Machine Learning or AI consultant. You will be assigned, from time to time, to selected client projects.
Your job begins after you successfully complete the 43-week Master ML & AI program, while maintaining a B+ or higher in aggregate for the program as a whole.
If you choose not to take the job after completing the program, you will lose your DSLP fellow status, and will owe us an up-front amount of INR 1,00,000, followed by monthly instalments equivalent to 17% of your monthly CTC or INR 20,000 - whichever is higher - for a period of 24 months (i.e. 24 such instalments) toward the tuition fee of the program.
The minimum obligation to work with us, under the DSLP fellowship, is 18 months.
If you choose to leave the job after 18 months, your notice period will be 3 months.
If you choose to leave any time prior, you will lose your DSLP fellow status, and will owe us an up-front amount of INR 1,00,000 followed by monthly instalments equivalent to 17% of your monthly CTC or INR 20,000 - whichever is higher - for a period of 24 months (i.e. 24 such instalments) towards the tuition fee of the program.
You can discontinue participation in the DSLP fellowship. In this case, and will owe us an up-front amount of INR 1,00,000 followed by monthly instalments equivalent to 17% of your monthly CTC or INR 20,000 - whichever is higher - for a period of 24 months (i.e. 24 such instalments) towards the tuition fee of the program.
Students who are not able to meet the required academic standards to maintain their program status throughout the duration of the fellowship, due to legitimate reasons, will be considered on a case by case basis.
The majority of our clients are overseas. It is likely, once travel conditions in the world become conducive, that your assignments will involve overseas work.
Depending on the selection of projects available, we may be able to accommodate your request to work in your area of interest.
It is our recommendation that you do not wait until you receive the results of your DSLP application, to submit a regular application. Seats are limited and may no longer be available. If you get accepted into both the programs, you will have the opportunity to make a choice.