Data Scientist

Astra Tech; Abu Dhabi; On-site; AED 180,000 - 250,000; Full time

Job summary

A leading tech company in Abu Dhabi seeks a Data Analyst to extract insights from large datasets. The role requires strong statistical and machine learning skills, with responsibilities including data preparation, model building, and visualization. Ideal candidates have a Master’s degree and 7+ years of relevant experience, focusing on driving data-informed decisions and strategies.

Qualifications

• Master’s degree preferred, 7+ years in technology platforms.
• Experience in Python, R, and machine learning.
• Strong background in data management and visualization.

Responsibilities

• Gathering and cleaning data from various sources.
• Building and validating statistical models and algorithms.
• Communicating findings to stakeholders.

Skills

Python

R

scikit-learn

data-modelling

machine-learning

data visualization

Education

Master’s degree in Computer Science, Computer Engineering, Mathematics or Statistics

Tools

SQL

Big data technology suites

Job description

About Us

Established in 2022, Astra Tech has rapidly expanded its influence by strategically acquiring and developing key platforms such as PayBy, Rizek, Quantix, and Botim. These acquisitions have culminated in the creation of the world’s first Ultra App, Botim, which seamlessly integrates fintech, e-commerce, AI-powered tech solutions, and communication services into one intuitive and user-friendly experience. This powerful combination allows users to manage their finances, shop, and stay connected—all within a single, cohesive platform.

With over 150 million users across 155 countries, Astra Tech is more than just a tech company—it is a movement committed to enhancing lives through innovation. As a visionary leader in tech development and investment, our mission is clear: to revolutionize technology solutions for consumers and businesses, harnessing the power of AI to elevate digital experiences to unprecedented heights globally.

Role Summary

Extracting knowledge and insights from data to support organizational goals by collecting, cleaning, analysing, and interpreting large datasets using statistical, machine learning, and programming skills.

Responsibilities

• Data Collection and Preparation: Gathering data from various sources, cleaning and transforming it for analysis.
• Exploratory Data Analysis (EDA): Investigating data to identify patterns, trends, and anomalies.
• Model Building and Evaluation: Developing and validating statistical models and machine learning algorithms.
• Data Visualization: Creating clear and informative visualizations to communicate findings to stakeholders.
• Stakeholder Communication: Presenting results and recommendations to both technical and non-technical audiences.
• Strategic Recommendations: Providing data-driven insights to guide business decisions and strategies.

Requirements

• Master’s degree in Computer Science, Computer Engineering, Mathematics or Statistics preferred.
• Experience 7+ years in consumer technology platforms.
• Experience developing in Python, R, scikit-learn with demonstrated knowledge of good software engineering design principles.
• Experience working with Big data technology suites.
• Experience working with relational databases, SQL, data-modelling and dealing with large, complex, structured, and unstructured datasets.
• Extensive familiarity with machine-learning concepts and applications.
• Build statistical, predictive and machine learning models to facilitate Strategy, Product, Marketing, Sales, Customer Service and Technology teams drive business growth.
• Develop analytics-oriented solutions to solve complex business problems leading to data-driven decision making.
• Storyboard visualizations to educate stakeholders on findings.
• Support data activities related to the collection, profiling, cleansing, and reporting of analytical models.
• Participate in planning sessions with key stakeholders to develop use cases and requirements for data-driven analytical solutions.
• Experience developing automating data pipelines as an asset.