Entry Level Data Analyst

About the Role

Matricstek Inc. is looking for a meticulous and insightful Data Analyst to join their expanding team in Boston, MA. This position involves gathering, cleaning, and interpreting extensive datasets to support strategic business decisions. The role requires close collaboration with various departments to identify key trends, develop reports, and generate actionable intelligence aimed at enhancing business operations and results.

Responsibilities

• Gather, cleanse, and confirm data integrity from diverse sources to maintain consistent and accurate datasets.
• Examine substantial datasets to reveal trends, patterns, and business possibilities.
• Create interactive dashboards, reports, and visual presentations utilizing BI tools like Tableau or Power BI.
• Compose advanced SQL queries to efficiently retrieve and manage data.
• Work with stakeholders to comprehend reporting needs and key performance indicators (KPIs).
• Conduct statistical evaluations and communicate insights clearly and succinctly.
• Facilitate data-informed decision making throughout departments such as finance, operations, marketing, and product development.
• Automate repetitive reporting tasks and enhance data workflows for greater efficiency.
• Oversee data quality and resolve inconsistencies or irregularities.
• Maintain documentation for data definitions, processes, and analysis methodologies.

Qualifications

• Bachelor’s degree in Data Analytics, Computer Science, Statistics, Mathematics, Information Systems, or related discipline.
• Solid proficiency in SQL and understanding of database structures.
• Experience with Excel and visualization platforms including Tableau or Power BI.
• Knowledge of Python or R programming languages is advantageous.
• Grasp of statistical methods and data modeling approaches.
• Strong analytical thinking, problem-solving ability, and communication skills.
• Capacity to work both independently and as part of a team in a dynamic environment.
• Familiarity with cloud computing environments such as AWS, Azure, or Google Cloud.
• Understanding of ETL (Extract, Transform, Load) procedures and data warehousing principles.
• Basic exposure to machine learning concepts and predictive analytics techniques.
• Experience handling large structured and unstructured data sets.