Sr. Data Analyst – Risk Data Projects

Dicetek LLC is seeking a Sr. Data Analyst for Risk Data Projects in Dubai, UAE. The role involves organizing and analyzing data related to sales, market research, and logistics, ensuring data accuracy, and presenting insights to aid decision-making. Key responsibilities include data cleaning, statistical analysis, database management, and creating reports and dashboards. Essential skills include programming in Python and R, SQL, and familiarity with data visualization tools.
Data Analyst A data analyst is responsible for organizing data related to sales numbers, market research, logistics, linguistics, or other behaviors. They utilize technical expertise to ensure data is accurate and high-quality. Data is then analyzed, designed, and presented in a way that assists individuals, businesses, and organizations make better decisions.Using automated tools to extract data from primary and secondary sourcesRemoving corrupted data and fixing coding errors and related problemsDeveloping and maintaining databases, and data systems – reorganizing data in a readable formatPerforming analysis to assess the quality and meaning of dataFilter Data by reviewing reports and performance indicators to identify and correct code problemsUsing statistical tools to identify, analyze, and interpret patterns and trends in complex data sets could be helpful for the diagnosis and predictionAssigning numerical value to essential business functions so that business performance can be assessed and compared over periods of time.Analyzing local, national, and global trends that impact both the organization and the industryPreparing reports for the management stating trends, patterns, and predictions using relevant dataWorking with programmers, engineers, and management heads to identify process improvement opportunities, propose system modifications, and devise data governance strategies.Preparing final analysis reports for the stakeholders to understand the data-analysis steps, enabling them to take important decisions based on various facts and trends.Another integral element of the data analyst job description is EDA or Exploratory Data Analysis Project. In such data analyst projects, the analyst needs to scrutinize data to recognize and identify patterns. The next thing data analysts do is use data modeling techniques to summarize the overall features of data analysis.Essential Data Analyst SkillsData analysts need a mix of technical, analytical, and soft skills to effectively analyze data and communicate their findings. Here are some essential skills for data analysts: Data Cleaning and PreparationData analysts should know how to clean and prepare data for analysis. This includes removing errors, identifying outliers, and transforming data into a format that can be analyzed. Data Analysis and ExplorationData analysts need to be able to analyze data and explore it for insights. This includes using statistical methods to test hypotheses, identify trends, and make predictions. Statistical AnalysisUnderstanding statistical tests and tools is crucial. Familiarity with mean, median, variance, standard deviation, correlation, regression, and hypothesis testing can be fundamental. ProgrammingKnowledge Of Programming Languages, EspeciallyPython: Libraries like pandas, numpy, and scikit-learn are essential for data manipulation and analysis.R: Another powerful language for statistical analysis and data visualization. Database ManagementThe ability to query databases using SQL is essential for extracting data.Knowledge of database systems like MySQL, PostgreSQL, Oracle, or MS SQL. Creating Dashboards and ReportsData analysts need to be able to create dashboards and reports that communicate insights to stakeholders. This includes using tools like Tableau, Power BI, and Microsoft Word to create interactive dashboards and reports. Data VisualizationUsing tools and libraries like Tableau, Power BI, Matplotlib, Seaborn, or ggplot2 to represent data in a visual format thats easy to understand. Machine LearningMachine learning is a growing field that is becoming increasingly important for data analysts. Data analysts who are proficient in machine learning can use it to automate tasks, identify patterns, and make predictions. ExcelOften overlooked, but its still widely used for data analysis and visualization, especially in smaller datasets or in business settings.Experience: 8-9 years’ experience as a Data Analyst, preferably in Banking field, especially in Risk Domain.CommunicationSkills / Competencies: Explains or presents factual information to individuals or groups in a structured, clear, confident and concise way; explains the reasoning about what is being said to ensure understanding and acceptanceProduces clear and concise reports and other written material usually of a detailed and technical nature, which are understandable to those with or without a good knowledge of the subject matterAnalytical Thinking And Problem SolvingIs detail-oriented and capable of delivering a high level of accuracyBrings innovation to problem solvingInterpersonal SkillsHas the ability to run stakeholder meetingsIs assertive