Data Scientist

GAL; Abu Dhabi; On-site; AED 200,000 - 300,000; Full time

Job summary

A data analytics company in Abu Dhabi is seeking a Data Scientist to extract insights from structured and unstructured data. The successful candidate will build predictive models, perform statistical analysis, and support data-driven decisions. Responsibilities include collecting and analyzing large datasets, developing machine learning algorithms, and communicating insights through visualizations. Candidates should have strong programming skills in Python or R and a bachelor’s degree in Data Science or a related field. Experience ranging from 3–7 years is preferred.

Qualifications

• 3–7 years of experience in Data Science or Analytics roles.
• Proven experience analyzing large datasets and delivering insights.
• Hands-on experience building predictive and statistical models.

Responsibilities

• Collect, clean, analyze, and interpret large datasets from multiple sources.
• Develop statistical models and predictive analytics solutions.
• Build dashboards and visualizations to communicate insights.

Skills

Python

R

Machine Learning

Data Visualization

SQL

Statistical Analysis

Data Manipulation

Education

Bachelor’s degree in Data Science or related field

Master’s degree or PhD in Data Science, Statistics, or related field

Tools

Scikit-learn

TensorFlow

PyTorch

Pandas

NumPy

Power BI

Tableau

Job description

Data Scientist is responsible to extract insights from structured and unstructured data, build predictive models, and support data-driven decision-making across the organization. The role involves applying statistical analysis, machine learning, and data visualization to solve complex business problems.

DUTIES AND RESPONSIBILITIES

1. Collect, clean, analyze, and interpret large datasets from multiple sources.
2. Develop statistical models, machine learning algorithms, and predictive analytics solutions.
3. Perform exploratory data analysis (EDA) to identify patterns, trends, and anomalies.
4. Translate business requirements into analytical and data science solutions.
5. Build dashboards, reports, and visualizations to communicate insights to stakeholders.
6. Collaborate with data engineers and software developers to deploy models.
7. Validate and monitor model performance and accuracy.
8. Ensure data quality, governance, privacy, and compliance.
9. Document methodologies, models, and assumptions.

SUPERVISORY RESPONSIBILITY

May lead small team of Data Scientist Team in delivering project modules

COMMUNICATIONS

Must be able to communicate well in English language in order to write software technical documentation, create coding standards & instructions and to effectively interact with Project Lead, Development team and Technical staffs. Knowledge of Arabic is a plus.

OTHER FACTORS

1. Master’s degree or PhD in Data Science, Statistics, or related field.
2. Experience with Big Data tools (Spark, Hadoop).
3. Knowledge of data governance, data ethics, and explainability.
4. Relevant certifications in Data Science or Analytics.

Nationality

No Restriction

QUALIFICATIONS

Minimum Qualification:

Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.

Strong programming skills in Python or R.

Solid understanding of statistics, probability, and data analysis techniques.

Experience with machine learning libraries: Scikit-learn, TensorFlow, PyTorch (as applicable).

Proficiency in data manipulation and analysis tools (Pandas, NumPy).

Experience with data visualization tools (Power BI, Tableau, Matplotlib, Seaborn).

Strong SQL skills; familiarity with NoSQL databases is a plus.

Knowledge of cloud data platforms (AWS, Azure, GCP).

EXPERIENCE

3–7 years of experience in Data Science, Analytics, or related roles.

Proven experience analyzing large, complex datasets and delivering actionable insights.

Hands-on experience building and validating predictive and statistical models.

Experience applying machine learning techniques in real-world use cases.

Experience working with business stakeholders to define analytical requirements.

Experience deploying models or analytics solutions into production environments is preferable.

Exposure to NLP, Time-Series Analysis, or Big Data technologies is a plus.

Experience in enterprise, government, or regulated environments is an advantage.