Data Scientist Job in Ras Al Khaimah

A leading and innovative company in the Emirate of Ras Al Khaimah is now accepting applications for the position of Data Scientist within its technology and analytics team. This opportunity arises at a time when the region is undergoing rapid digital transformation, with data becoming the core driver for strategic decision-making and creating sustainable competitive advantage.

Job Description

The appointed Data Scientist will play a vital role in extracting actionable insights from complex and large-scale datasets. The successful candidate will work closely with business and development teams to understand challenges and transform them into opportunities using statistical analysis and machine learning techniques.

Key Expected Responsibilities:

• Collect, clean, and analyze large datasets from various internal sources.
• Develop and deploy predictive models and machine learning algorithms to optimize business processes and decision-making.
• Design and implement experiments (A/B Testing) to measure the effectiveness of various initiatives.
• Create dashboards and visual reports (Data Visualization) to communicate complex findings to non-technical stakeholders in a clear and impactful manner.
• Stay up-to-date with the latest trends and technologies in data science and artificial intelligence.
• Contribute to building a data-driven culture within the organization and promoting the adoption of analytics across all departments.

Requirements and Qualifications

The company is looking for candidates with a genuine passion for data and the ability to turn numbers into stories and strategies.

Academic Qualifications:

• A Bachelor's or Master's degree in a relevant field such as: Computer Science, Statistics, Mathematics, Engineering, or any other quantitative field.
• Previous practical experience in a similar role (Data Scientist, Advanced Data Analyst) will be a significant advantage.

Required Technical Skills:

• Strong proficiency in data science programming languages such as Python or R, with a focus on libraries like Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch.
• Hands-on experience in writing and querying databases using SQL.
• Deep understanding of machine learning techniques (supervised and unsupervised) and statistics.
• Proficiency in using data visualization tools like Tableau, Power BI, or libraries like Matplotlib and Seaborn.
• Knowledge of big data processing concepts and tools (e.g., Spark) will be a valuable addition.

Personal Skills:

• Exceptional analytical and deductive reasoning skills.
• Ability to solve complex problems in a creative way.
• Excellent communication skills, both verbal and written, for presenting technical results.
• Ability to work collaboratively within a team as well as independently.
• Intellectual curiosity and a continuous desire to learn and develop.

Work Location and Benefits

• Work Location: Ras Al Khaimah, United Arab Emirates. Ras Al Khaimah is known for its stunning natural environment and competitive cost of living, offering an excellent work-life balance.
• Work Environment: Join a dynamic and innovative team within a company that invests in technology and talent.
• Career Development: Opportunities for growth and advancement in a fast-evolving field like AI and data science.

How to Apply

Applications for this exclusive position are submitted via the Naukrigulf platform. Please search for the job under the title "Data Scientist" in the Ras Al Khaimah location, or follow the direct link if available. Ensure your Curriculum Vitae (CV) is updated to highlight relevant projects, the technical skills mentioned, and measurable past achievements. Attaching a portfolio or links to projects on platforms like GitHub is preferred to demonstrate practical experience.

As the company name is confidential, the initial screening process will focus heavily on the skills and experience outlined in your resume. Make sure to craft your Cover Letter to clarify your passion for the data field and how your skills can add immediate value to the team.