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 Lead Data Scientist with experience in various data science techniques, tools, and cloud providers.
The ideal candidate will be responsible for designing, developing, and implementing cutting-edge data science models and machine learning algorithms to tackle complex problems in various domains. You will work closely with cross-functional teams to understand business requirements, identify opportunities for applying machine learning/deep learning/AI techniques, and deliver innovative solutions that push the boundaries of AI technology. This role requires a strong background in machine learning, deep learning, and computer vision, along with a passion for exploring and experimenting with state-of-the-art models.
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Responsibilities
- Design, develop, and implement novel data science models and machine learning algorithms that solve complex problems. This includes architectural design, data preprocessing, training, optimization, and evaluation of models
- Collaborate with data engineers and data scientists to collect, pre-process, and curate datasets suitable for training
- Train and fine-tune machine learning/deep learning models using large-scale datasets and distributed computing frameworks. Optimize models for performance, efficiency, and scalability
- Design and conduct experiments to evaluate the performance, robustness, and generalization of tune machine learning/deep learning models
- Use appropriate metrics and statistical analysis to measure and interpret results
- Prepare technical documentation, including model architecture, implementation details, and experimental results. Communicate findings, insights, and recommendations to both technical and non-technical stakeholders
- Bachelor's or master's degree in computer science, Data Science, Statistics, or related field
- 8 to 12 years of solid foundation in Machine Learning, Deep Learning, Computer Vision, NLP
- Proficiency in Python
- Experience Deep learning framework like Tensorflow, Pytorch, Keras, Jax, etc
- Experience with pandas, scikit-learn, matplotlib, spacy, statsmodel, etc
- General understanding of data structures, algorithms, multi-threaded programming, and distributed computing concepts
- Knowledge of statistical and algorithmic models as well as of fundamental mathematical concepts, such as linear algebra and probability
- Familiarity with cloud services (AWS, Google Cloud, Azure)
- Excellent written and verbal communication skills
- Good to have - Docker, Kubernetes
- 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.)