Data Analyst

Job Description: • Understanding the business requirements so as to formulate the problems to solve and restrict the slice of data to be explored. • Support and partner with teams across the enterprise. • Support and contribute to data collection efforts, as needed. • Verify data quality to ensure accurate analysis and reporting. • Performing cleansing, processing, and validation on the data subject to analyze, in order to ensure its quality. • Help identify the business data needed to produce the most useful insights and future analytics. • Utilize data to make actionable recommendations at all levels. • Develop and execute a regional business plan aligning with program goals. • Communicate insights and recommendations effectively to the broader team. • Monitor data management processes to ensure data quality and consistency. • Hire, coach and develop field to exceed customer expectations. • Monitor system performance, data integrity and usage metrics. • Contribute to data dictionary, standards, training, and ongoing updates. • Analyzing local, national, and global trends that impact both the organization and the industry • Preparing reports for the management stating trends, patterns, and predictions using relevant data • Working 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. Qualifications: • Bachelor's or Graduate's Degree in business, computer science, engineering, or information systems or equivalent experience. • Comfortable with statistics, datasets, and machine learning exercises. • Strong critical thinking skills and attention to detail. • Has consulting experience and ability to assist with problem solving and debugging. • A leader and critical thinker with time management skills. • Experience solving problems in the project’s business domain. • Proficiency in at least one query language, especially SQL. • Experience with NoSQL databases, such as MongoDB and Cassandra. • Experience with popular statistical and machine learning techniques, such as clustering, linear regression, KNN, decision trees, etc. • Good scripting skills. • Proficiency in at least one data visualization tool, such as Matplotlib, Plotly, D3.js, ggplot, etc. • Experience with BI tools such as Tableau and Power BI. • Great communication skills.