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.

Qualifications:

To qualify, you must have:
- 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.

Ideally, you'll also need:
- 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.