Junior Data Analyst (Data Scientist)

Company not disclosed

United Arab Emirates
Salary not specified
Posted
Full-time
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Job Description

Company Description - This opportunity is advertised on behalf of a partner company. All applications, interviews, and subsequent hiring steps will be managed directly by the partner organization. - Our partner is seeking a Junior Data Analyst / Data Scientist to join their remote team and contribute to data-driven projects across Financial Services, Retail, E-commerce, Logistics, Business Intelligence, Artificial Intelligence (AI), and Machine Learning (ML). - This role is well suited to an early-career data professional who is curious about how data can be used to solve business problems, uncover trends, and support better decision-making. - The successful candidate will have the opportunity to work on a variety of analytics and data science projects, ranging from business reporting and data visualization to predictive modeling and machine learning. Key Responsibilities - Collect, clean, transform, and analyze data from different internal and external sources - Use Python, SQL, and statistical techniques to investigate business and operational questions - Conduct Exploratory Data Analysis (EDA) to uncover trends, relationships, anomalies, and opportunities - Build and maintain reports, dashboards, KPIs, and Business Intelligence (BI) solutions - Perform descriptive and statistical analyses to support business and strategic decisions - Assist in developing and evaluating Machine Learning (ML) and predictive models - Contribute to customer, product, commercial, marketing, and operational analytics projects - Analyze areas such as customer behavior, transactions, sales performance, product usage, and operational efficiency - Support forecasting, customer segmentation, classification, and other predictive analytics initiatives - Assist with A/B testing, experimentation, and hypothesis-driven analysis - Develop clear and meaningful data visualizations to communicate analytical findings - Present insights and recommendations to both technical and non-technical stakeholders - Contribute to AI, automation, and other data-driven initiatives - Help identify opportunities to improve data quality, reporting processes, and analytical workflows - Work collaboratively with teams across Product, Engineering, Finance, Marketing, Operations, and Business - Translate business requirements and questions into structured analytical approaches Requirements - Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, Engineering, Business Analytics, Information Systems, or another quantitative discipline - Solid foundational knowledge of Python and SQL - Good understanding of statistics, probability, and fundamental data analysis concepts - Hands-on experience working with datasets and conducting Exploratory Data Analysis (EDA) - Familiarity with Python data and Machine Learning libraries such as pandas, NumPy, and scikit-learn - Experience with or understanding of dashboarding and reporting tools such as Power BI, Tableau, Looker, or similar platforms - Strong analytical thinking and problem-solving abilities - Ability to interpret data and communicate insights in a clear and structured manner - Strong written and spoken English - Comfortable working both independently and as part of a distributed, remote team Preferred Qualifications - Internship, academic, bootcamp, freelance, or personal project experience in Data Analytics, Data Science, Business Intelligence, or Machine Learning - Exposure to data-driven industries such as Financial Services, FinTech, Retail, E-commerce, Logistics, or Technology - Familiarity with Git and GitHub - Experience working with Jupyter Notebook - Basic exposure to cloud environments such as AWS, Microsoft Azure, or Google Cloud Platform (GCP) - Familiarity with modern data warehouses and platforms including BigQuery, Snowflake, Redshift, or Databricks - Experience using Excel or BI and visualization tools such as Power BI, Tableau, or Looker - Exposure to predictive modeling, Machine Learning, or statistical modeling techniques - Familiarity with Generative AI, Large Language Models (LLMs), or AI-based applications - Portfolio demonstrating practical data work, such as GitHub repositories, Kaggle notebooks, university assignments, bootcamp projects, or personal Data Analytics / Data Science projects

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