Senior Applied Scientist

Overview

Looking for an astute, insightful and innovative Senior Applied Scientist to lead and execute data analytics and business intelligence projects for G42's diverse clients, leveraging AI-driven solutions to address their unique challenges and opportunities. You will be responsible for developing and implementing cutting-edge data analysis models, creating data visualizations, and providing strategic recommendations to clients across multiple industry verticals.

Responsibilities

'Functional:

• Lead and participate in end-to-end data analytics and business intelligence projects, from data collection and preprocessing to modeling, analysis, and reporting, employing statistical methods, machine learning algorithms, and data mining techniques.
• Collaborate with cross-functional teams to understand client requirements, design solutions, and deliver actionable insights.
• Develop and maintain scalable data pipelines and analytics infrastructure for efficient data processing and analysis.
• Design and develop AI models for predictive analytics, anomaly detection, and pattern recognition.
• Collaborate with clients to identify business objectives and translate them into data analysis and reporting requirements.
• Create and maintain dashboards and reports to visualize and communicate data-driven insights.
• Ensure data quality and accuracy by implementing data cleansing, transformation, and validation processes.
• vContinuously evaluate and enhance data analytics processes, tools, and techniques to optimize efficiency and effectiveness.
• Present findings and recommendations to clients in a clear and understandable manner, tailoring communication to various stakeholders.
  
  

• A Ph.D. or Master's degree in a relevant field such as Computer Science, Data Science, Statistics, or a related discipline.
• Minimum of 7 years of experience in data analytics, business intelligence, or related roles, with a strong background in AI and machine learning applications.
• Proficiency in programming languages such as Python and R, as well as data analysis libraries (e.g., Pandas, NumPy, Scikit-Learn).
• Hands-on experience with data visualization tools (e.g., Tableau, Power BI) and database management systems (e.g., SQL).
• Experience in working with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and big data technologies.
  
  

• Strong problem-solving skills and the ability to work with complex, large-scale datasets.
• Excellent communication skills to effectively convey technical findings and insights to non-technical stakeholders.
• Strong project management and leadership skills to guide interdisciplinary teams and drive project success.
• Exceptional teamwork and interpersonal skills to foster collaboration and maintain strong client relationships.