Lead Data Scientist (Data GTS)

at  Epam Systems

We invite applications for the position of Lead Data Scientist (Data GTS). The ideal candidate will possess robust expertise in Python and SQL and be comfortable working remotely with our team.
In the role of Lead Data Scientist, your primary responsibilities will include identifying business-related issues, conducting comprehensive data analysis, creating and validating models, and succinctly presenting findings. Your contributions will significantly influence our organization’s data-driven decision-making processes.
We eagerly await your application to bring your expertise on board!

REQUIREMENTS

• Minimum 5 years of experience in Python and SQL for data analysis and modeling
• At least 1 year of relevant leadership experience
• Significant experience in data-focused applied mathematics, including statistical analysis and machine learning
• Proficiency in modeling and Algorithm approach, such as Boosting Algorithms
• Familiarity with data analysis tools and libraries, including NumPy, SciPy, Scikit-learn, pandas, and matplotlib
• Strong experience in ML Modeling for Deep Learning, AI, and Time Series Forecasting
• Expertise in at least one of the major Cloud providers (AWS, GCP, or Azure)
• Knowledge of productionalizing Data Science solutions
• Proficient data visualization skills
• Experience with NLP and text mining
• Problem-solving aptitude
• Strong communication and presentation skills, with fluency in English

• Identification and addressing of business issues through data analysis and modeling
• Effective utilization of Python and SQL for data interpretation and analysis
• Creation and validation of analytical models for various applications, including Deep Learning, AI, and Time Series Forecasting
• Clear and informative presentation of findings and insights
• Collaboration with cross-functional teams to promote data-driven decision-making
• Staying abreast of the latest developments in Data Science and ML modeling
• Contribution to the productionalization of Data Science solutions
• Effective visualization of data to communicate insights
• Application of NLP and text mining techniques for insightful decisions
• Leadership and mentorship for junior data science professionals