Data Scientist (Kaggle, MLE) Bangalore, India
Data Scientist (Kaggle, MLE) Description
EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
We are seeking a talented Data Scientist to become an integral part of our team.
Within the Kaggle team, the Data Scientist will play a pivotal role in managing the publication and maintenance of machine learning models.
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Responsibilities
- Publish machine learning and LLM models on Kaggle through APIs or manually
- Create educational materials such as step-by-step guides and interactive notebooks to aid in understanding and applying machine learning models
- Work collaboratively to define metrics and improve the model publishing workflow
- Keep up-to-date with the latest developments in machine learning models
- Assess and choose models to publish based on performance, usability, and potential impact
- Engage with internal and external stakeholders to receive feedback and enhance the model publishing process
Requirements
- Minimum of 3 years in data science and machine learning
- Bachelor’s degree in Computer Science, Data Science, or a related field
- Proficiency in Python and various machine learning frameworks like Keras, PyTorch, Transformers, etc
- Solid background in natural language processing, computer vision, and large language models
- Strong communication and teamwork skills
- Capability to work independently and collaboratively
- B2+ English proficiency level
Nice to have
- Previous experience with the Kaggle platform, including participation in competitions, exploration of datasets, notebooks, or models
We offer
- Opportunity to work on technical challenges that may impact across geographies
- Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications
- Opportunity to share your ideas on international platforms
- Sponsored Tech Talks & Hackathons
- Unlimited access to LinkedIn learning solutions
- Possibility to relocate to any EPAM office for short and long-term projects
- Focused individual development
- Benefit package:
- Health benefits
- Retirement benefits
- Paid time off
- Flexible benefits
- Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)
