DayToDay Responsbilities:

• Collaborate with business stakeholders to understand their data needs and requirements, and translate them into actionable insights and data-driven solutions.
• Perform data analysis tasks, including data cleaning, data transformation, and data visualization, to uncover meaningful patterns and trends in large datasets.
• Partner with data engineering to develop and maintain data pipelines and workflows, ensuring efficient and accurate data extraction, transformation, and loading (ETL) processes.
• Apply statistical analysis techniques and machine learning algorithms to identify correlations, predict outcomes, and optimize business processes.
• Assist in the development and maintenance of data models, data dictionaries, and data documentation to ensure data integrity and consistency.
• Conduct exploratory data analysis to discover insights and provide recommendations for improving business performance and decision-making.
• Collaborate with data engineers and data scientists to identify opportunities for automation and optimization of data processes and workflows.
• Monitor data quality and proactively identify and resolve data discrepancies or anomalies.
• Participate in cross-functional teams to support data-related projects, providing expertise and guidance on data analysis, data management, and data visualization.
• Work on business case development, project value proposition, and help with workload prioritization.
• Stay updated with the latest industry trends and advancements in data analytics, data science, and data engineering, and apply this knowledge to enhance data capabilities within the organization.
• Constant, self-motiviated pursuit of learning systems, organizational structure, processes, data sets, techniques, etc.
• Interpret and explain information to audiences who are not familiar with the subject matter, often requiring persuasion.
• Is required to review and recommend solutions to issues that involve a number of possible alternatives which may not be clearly defined.
• Serve as a project lead or task force member on projects and/or issues having a significant impact on functional and strategic goals.
• Provide guidance and training to others in the use of new technologies, theories, concepts and techniques.
• Constant, self-motiviated pursuit of learning systems, organizational structure, processes, data sets, techniques, etc.
• Operate with limited supervision, guidance, and direction from leadership and senior staff.
• Provide training and guidance to less experienced professionals

Must Have:

• Bachelor's degree from an accredited college or university in Data Science, Analytics, Mathematics, Statistics, Computer Science, or a related field.
• Requires a minimum of 5 years of related experience.
• Strong proficiency in Data visualization software like PowerBI, Tableau, and Looker.
• Strong proficiency in Cloud Computing Platofrms such as GCP, Azure, and AWS.
• Experience with Data Warehousing technology like Oracle Databases, SAP HANA, BigQuery
• Strong proficiency in SQL for data querying and manipulation.
• Strong in programming languages such as Python and R for data analysis and scripting.
• Understanding of data modeling concepts and experience with data modeling tools.
• Experience working with machine learning, statistical techniques and algorithms
• Proficiency in ETL processes, data warehousing, and database management systems.
• Excellent problem-solving and analytical skills, with attention to detail
• Experience interacting with employees of all levels to present technical data in a non-technical manner.
• Strong communication skills, with the ability to translate complex data concepts into understandable insights for non-technical stakeholders.