AI Data Scientist

Location: Fully on site in Dubai

Rate: 30k - 42k

The AI Data Scientist will play a pivotal role in processing and analyzing

large datasets, developing predictive models, and extracting actionable insights to drive

business decisions. This position involves working closely with data engineers, AI engineers,

and software developers to build and maintain robust data solutions that support our AI and

data initiatives.

Key Responsibilities:

1. Data Processing & Management:

○ Design, develop, and maintain scalable data processing pipelines for handling

large datasets using both on-premise and cloud platforms (e.g., AWS).

○ Ensure data quality, consistency, and accuracy through rigorous validation and

cleansing processes.

2. Data Analysis & Insights:

○ Monitor and perform comprehensive data analysis to identify trends, patterns,

and correlations within large datasets.

○ Generate actionable insights and present findings to stakeholders through clear

and concise visualizations.

3. Model Development:

○ Develop, test, and deploy predictive models with (deep) machine learning

algorithms using frameworks such as TensorFlow, PyTorch, and Scikit-learn.

○ Continuously monitor and refine models to improve performance and accuracy.

4. Collaboration and Support:

○ Work closely with data engineers, AI engineers, and software developers to

understand data requirements and provide technical support.

○ Facilitate effective communication and collaboration within the AI and data teams

and other technical teams.

5. Security and Compliance:

○ Ensure the security and compliance of data handling and processing by

implementing best practices and adhering to regulatory requirements.

○ Conduct regular audits and assessments to identify and mitigate security

vulnerabilities.

6. Continuous Improvement:

○ Identify areas for improvement in data processing, analysis, and model

development workflows.

○ Stay updated with the latest industry trends and technologies related to data

science and AI.

Experience:

● Minimum of 3-5 years of experience in data science, machine learning, or a similar role.

● Proven experience in processing and analyzing large datasets.

● Strong background in Python programming and data manipulation libraries (e.g.,

Pandas, NumPy).

Skills:

● Proficiency in machine learning frameworks and tools (e.g., TensorFlow, PyTorch, Scikit-

learn).

● Strong analytical and problem-solving skills with a meticulous and data-sensitive

approach.

● Excellent communication skills with the ability to convey complex data insights to non-

technical stakeholders.

● Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g.,

Apache Spark, Hadoop).

● Attention to detail and a patient, methodical approach to data handling and analysis.

Preferred Qualifications:

● Experience in fraud detection, recommendation systems, and predicting customer

behavior.

● Understanding of data engineering and MLOps methodologies.

● Awareness of security best practices in data environments.

● Proficiency with data visualization software (e.g., Tableau, Power BI).