Data Scientist

Job Title : AI Data Scientist / Data Engineer AI Location : Dubai, UAE
Company : Apparel Group
Job Purpose:
As a Data Scientist / Data Engineer at Apparel Group , you will play a critical role in designing, building, and managing the data infrastructure and analytics solutions that empower data-driven decision-making across the company. You will collaborate with cross-functional teams to deliver insights that optimize business operations, enhance customer experiences, and fuel innovation in the retail space. Your work will contribute to the creation of advanced data models, pipelines, and analytics tools to support strategic initiatives in merchandising, e-commerce, supply chain, and more.
Key Responsibilities:
For Data Scientist Focus:
Data Analysis & Modeling :
Develop predictive models using machine learning algorithms to enhance forecasting accuracy, inventory management, customer segmentation, and personalized recommendations.
Apply advanced analytics, including statistical modeling, clustering, classification, and anomaly detection, to extract actionable insights from complex datasets.
Design experiments (A/B testing) to measure the effectiveness of marketing strategies, promotions, and other business initiatives.
Data Visualization & Reporting :
Create dashboards and data visualizations to effectively communicate data-driven insights and KPIs to business stakeholders.
Work with BI tools such as Power BI, Tableau, or Looker to create intuitive and accessible data representations that aid decision-making.
AI & Machine Learning :
Develop, train, and implement machine learning models to drive innovation in product recommendations, demand forecasting, dynamic pricing, and supply chain optimization.
Collaborate with engineering teams to deploy models in production environments and ensure their scalability and robustness.
For Data Engineer Focus:
Data Architecture & Infrastructure :
Design, build, and maintain scalable data pipelines and ETL processes to collect, process, and store large datasets from various sources (e.g., sales, inventory, e-commerce).
Develop data architectures that ensure data accuracy, security, and accessibility across the organization.
Work with cloud platforms such as AWS, Azure, or Google Cloud to optimize data storage, access, and processing.
Data Integration :
Integrate data from multiple sources, ensuring high quality and consistency across all business systems, including POS, ERP, CRM, and digital platforms.’
Collaborate with software engineers and IT teams to integrate real-time data streams for live analytics and decision-making.
Automation & Optimization :
Automate data collection, processing, and analytics workflows to ensure timely delivery of insights to business units.
Optimize existing data models, ETL processes, and pipelines to improve performance, reduce costs, and scale as the business grows.
Collaboration:
Work closely with cross-functional teams, including merchandising, marketing, finance, and operations, to understand business needs and deliver data solutions that drive business value.
Partner with AI and innovation teams to explore the application of machine learning models in real-world retail scenarios.
Communicate complex data findings and insights to non-technical stakeholders, ensuring data-driven strategies are clear and actionable.
Key Requirements:
Experience :
4+ years of experience in data science or data engineering roles, preferably in the retail, e-commerce, or consumer goods sectors.
Experience in building and deploying scalable machine learning models (Data Scientist role) or designing and managing data pipelines (Data Engineer role).
Skills :
For Data Scientists :
Proficiency in Python, R, or similar programming languages for data analysis and machine learning.
Strong knowledge of machine learning algorithms, statistical methods, and data mining techniques.
Experience with AI/ML frameworks such as TensorFlow, Keras, or PyTorch.
For Data Engineers :
Proficiency in SQL, Spark, Hadoop, or similar big data processing frameworks.
Experience with ETL processes, data warehousing solutions (e.g., Redshift, BigQuery), and data lake architectures.
Strong understanding of cloud-based data infrastructure (AWS, GCP, Azure).
General :
Strong analytical and problem-solving skills with the ability to work on large datasets and deliver impactful insights.
Familiarity with data visualization tools like Power BI, Tableau, or similar.
Understanding of database management systems and relational databases (e.g., MySQL, PostgreSQL).
Excellent communication skills, with the ability to translate technical data findings into business-friendly language.
Education :
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Engineering, or a related field.
Preferred Qualifications:
Experience working in a fast-paced retail or consumer-facing environment.
Knowledge of retail industry data sources, systems, and processes (e.g., POS, CRM, ERP).
Certifications in cloud technologies or data engineering tools are a plus.