Data Analyst

at  ColorPro Finishers

ColorPro Finishers, with over 40 years of proven reliability and experience with interior and exterior finishes, new and existing structures. We are a fully insured finishing company serving the North Eastern Tri-State area with the past 12 years in the Southern Florida regions.
As a Union and Non-Union company, ColorPro Finishers has the ability to provide the flexibility of offering either Union or Non-Union labor depending on our clients’ requirements as well as to offer the right contract and most cost effect proposal to each client. Our skilled Non-Union employees provide superior expertise in all pohases of finishing projects, mainly high-end residential projects. Our expertise in painting and wall coverings is reinforced with our commitment to customer satisfaction. Painting quality and superior service are our priority.

JOB SUMMARY

You will uncover your own insights and proactively dig into data equipped with a high level of business context. You will help implement dashboards using query builders and SQL. In addition, you will work closely with product, engineering and design to ensure to we are collecting and storing the data we need to propel the business forward.

QUALIFICATIONS:

• Highly motivated, self-learner, and technically inquisitive
• Experience in programming language Java and understanding of the software development life cycle
• Project work on the skills
• Knowledge of Core Java , javascript , C+
• or software programming

• Data Exploration and Analysis: use statistical tools and techniques to explore and analyze data, identifying patterns, relationships, and trends.
• Data Visualization: create visual representations of data findings through charts, graphs, and dashboards to make the data understandable at a glance.
• Reporting: pepare reports and presentations to communicate the insights and findings from the data to stakeholders, which can influence product direction and decision-making processes.
• Collaboration: work with other departments to understand their data needs and help them make informed decisions based on data insights.
• Data Cleaning, Preparation, and Guidance: Filtering the data, handling missing values, and preparing the dataset for analysis to ensure accuracy and relevance, and providing feedback to engineering/product/design to improve data collection and handling.