11 Aug
|
Recognized
|
Sonipat
11 Aug
Recognized
Sonipat
> Position: Assistant
> Professor/Associate Professor/Professor
>
>
> Track: Data
> Engineering & Machine Learning
>
>
> Location: Sonepat,
> NCR of Delhi.
>
>
> Mode: Full Time;
> On -Campus
>
>
> Programme: B. Tech
> CS and Data Science
>
>
> ABOUT US
>
>
> Rishihood
> University
>
>
> Rishihood
> University (RU) has been established under The Haryana Private Universities
> (Amendment) Act, 2020 and is empowered to award degree as specified in section
> 22 of UGC Act, 1956.
>
>
> Rishihood
> University is India’s first and only impact university. ‘Impact’ is the living
> spirit of Rishihood. The purpose of education envisioned by the thought leaders
> of our civilization and that which has motivated the founders to build
> Rishihood University is beyond just awarding degrees and jobs. The purpose of
> education is to achieve the highest potential in a learner i.e., Rishihood.
> Rishihood University provides a unique mix of globally relevant education that
> is rooted in Indian ideas, quality education that is affordable, and a
> multi -disciplinary exposure with cutting edge skills of a specialist. To
> achieve this outcome, education cannot be limited to within the classrooms. RU
> is a fully residential campus where living and learning seamlessly integrate
> throughout the day. RU faculty and learners have an active participation with
> society, industry, researchers, entrepreneurs, and policy makers. This keeps
> the learning at RU focused on solving the biggest challenges faced by humanity
> and prepares our learners for the real world. It is time India builds
> universities driven by a higher purpose, that have a solid committed board to
> back it, that redefine the way education is imparted both within and outside
> the classroom. Rishihood is a bold initiative to fulfill this idea.
> Hence, we are looking for like -minded founding faculty members at Rishihood
> University.
>
>
> About Position
>
>
> Track | The
> DS Core
>
>
> Foundations of
> Data Science • Data Mining and Warehousing •
> Machine Learning • Supervised Learning
>
>
> India produces
> some of the world's best data scientists. Most of them were trained to use
> tools. We want to train students who can build the tools and understand deeply
> why they work. That is the difference between an execution hub and a technology
> defining nation. This track is where that shift starts.
>
>
> You will join Rishihood
> as a Faculty at the heart of what makes this a Data Science programme and not
> just another CS degree with a few ML electives tagged on. The DS Core takes
> students from raw data to predictive intelligence. As you grow into the Track
> Lead role, you will own this domain entirely: designing the learning arc from
> data foundations to production grade ML, building the faculty team, and holding
> the standard of every student who graduates from it.
>
>
>
>
>
>
>
>
>
> Requirements
>
>> Key
> Responsibilities
>
>>
>> 1. Teach Foundations
> of Data Science, Data Mining and Warehousing, Machine Learning, and Supervised
> Learning
>
>>
>> 2. Run labs that
> feel like real professional work: ETL pipelines with messy datasets, models
> that students deploy rather than just submit as notebooks
>
>>
>> 3. Guide capstone
> projects with rigorous validation: K fold cross validation, A/B testing, and
> production readiness checks
>
>>
>> 4. Lead MLOps
> integration into the curriculum and run seminars on data governance, GDPR,
> DPDP, and algorithmic fairness
>
>>
>> 5. Own curriculum
> design, faculty hiring, and the output standard for this track as Track Lead
>
>>
>>
>
>>
>> Job Specifications
>
>>
>> You should hold an
> MTech, PhD, or equivalent in a relevant field. Beyond the degree, here is what
> we actually care about.
>
>>
>> Technical Depth
>
>>
>> - Expert knowledge of supervised
> learning (Decision Trees, SVM, Random Forest, XGBoost, linear and logistic
> regression) and data engineering (Star and Snowflake schemas, ETL
> orchestration, Data Lakes vs Warehouses)
>
>> - Python data science stack: scikit
> learn, Pandas, NumPy, advanced SQL; model evaluation at depth: Precision
> Recall, F1 Score, ROC AUC, cross validation
>
>> - Working understanding of MLOps in
> practice and familiarity with cloud ML deployment on AWS SageMaker, Azure
> ML Studio, or GCP
>
>>
>> The Person
>
>> - You care about data quality as much
> as model sophistication, correct someone's thinking not just their code,
> and always ask whether it actually works when deployed
>
>> - You can translate real industry
> experience into classroom substance that students recognize as genuine
>
>>
>> Good to Have
>
>> - Industry experience as a Senior Data
> Engineer, ML Engineer, or ML Architect in a product based company
>
>> - Strong Kaggle ranking or open source
> ML contributions; experience deploying ML models at scale in cloud
> environments
>
>>
>> This job
> description is not intended to be all -inclusive. The employee may be expected
> to perform other duties as assigned by the supervisor.
>
>>
>>
>
>>
>>
>