Lead Data Scientist

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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• 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.)