Job Position: Data Scientist/Analyst Trainee
Qualification: B.Tech/ M.Tech/ MCA/MSc in computer science/IT/statistics/Data Science or equivalent from a top educational institution.
Industry Type: IT-Software, Software Services
Functional Area: IT Software – Application Programming, Maintenance
Employment Type: Full Time, Permanent
Role Category: Programming & Design
Job Location: Indore
- Strong programming skills. Knowledge of python is desirable.
- Knowledge of Machine learning/Deep Learning.
- Good understanding of statistics and time-series analysis concepts.
- Knowledge of any ML Frameworks such as Sckit-learn, Keras, and Tensorflow.
- Hands-on with common data science libraries such as Pandas, NumPy, SciPy, Matplotlib, seaborn, etc.
- Knowledge of NLP is plus includes spacy and nltk.
- Good understanding of database concepts and SQL.
- Knowledge of data visualization and BI tools such as Tableau, PowerBI is plus.
- Continuous learning attitude, data-oriented thought process, and ability to understand and implement research papers.
- Knowledge of cloud platforms AWS/GCP/Microsoft Azure is plus.
- Good communication skills.
- As a Trainee Developer for machine learning, you will work in a team of experienced researchers, data scientists, and application developers taking on challenges posed by the Yash customers and product units.
- You will work together with a team of dedicated experts including researchers, developers, DevOps engineers, and architects with a single goal of building the best machine learning pipelines for a variety of use cases spanning commerce, agriculture, Insurance, financial markets, and procurement.
- You will have the chance to work with the richest data sets available in the world addressing real-world problems.
- Your primary goal will be to implement state-of-the-art algorithms and to develop new approaches and technologies for deriving value from our customers’ data.
- You will have a chance to select and implement the best technologies and approaches based on your own experience, judgment, and experimentation results.