Identify use cases allowing to take advantage of GenAI & Machine Learning capabilities
Define data science approaches that fit with clients business challenges, using state-of-the-art methods to solve problems of large dimensionality in a computationally efficient and statistically effective manner.
Build advanced algorithms, using statistical knowledge and machine learning techniques to identify trends, patterns and predictive signals on large data sets
Interact with business stakeholders to understand business data and analytics requirements and identify data-driven business opportunities
Responsible for explores information from multiple diverse sources, analyzing data and gain insights into business intelligence that is actionable
Identify and uncover new opportunities, insights, trends, and patterns from analysis to key stakeholders/decision-makers
Stay up-to-date with the latest data science and data engineering techniques and tools
Deploy ML models into production (either alone or working with data engineers if necessary)
Requirements
Degree in Computer Science, Computer Engineering or a related field
Over 8 years expertise in Data Science and Data Analytics.
Strong understanding of programming languages such as Python, R, or SQL.
Proficiency in statistical analysis, machine learning algorithms, and data visualization techniques.
Excellent leadership and team management skills, with the ability to motivate and inspire a team of data scientists.
Strong communication and presentation skills, with the ability to convey complex concepts to non-technical stakeholders.
Proven track record of successfully leading and delivering data science projects and initiatives.
Experience working Agile and DevOps; familiar with DataOps.
Must be able to work collaboratively with cross-functional cross-geographical teams to analyze and understand business needs.
Good oral and written English: ready to present to a technical audience.
