Job Description
Welcome to Cleveland Data Insights, where we turn complex information into actionable business strategies. We are currently seeking a highly motivated Data Analyst to join our dynamic team in Cleveland, Ohio. We pride ourselves on offering a transparent compensation structure, including a competitive weekly paycheck, ensuring you are rewarded for your hard work every seven days.
As a Data Analyst, you will play a pivotal role in interpreting data and presenting it to stakeholders to drive strategic decision-making. If you are passionate about data, possess a keen eye for detail, and want to join a company that values consistency and growth, we want to hear from you.
Responsibilities
- Analyze Complex Datasets: Gather, clean, and interpret large sets of data to identify trends, patterns, and anomalies.
- Visualize Data: Create clear and compelling data visualizations using tools like Tableau or PowerBI to communicate insights effectively.
- Develop Dashboards: Build and maintain interactive dashboards that allow non-technical stakeholders to monitor key performance indicators (KPIs).
- SQL & Reporting: Write complex SQL queries to extract data from relational databases and generate weekly performance reports.
- Collaborate with Teams: Partner with product managers and engineering teams to define data requirements and improve data collection processes.
- Forecasting: Use statistical methods to predict future trends and support business planning.
Qualifications
- Education: Bachelor’s degree in Mathematics, Statistics, Computer Science, or a related field (or equivalent work experience).
- Experience: Minimum of 2 years of experience in data analysis, business intelligence, or a similar role.
- Technical Skills: Proficiency in SQL (PostgreSQL, MySQL) and programming languages such as Python or R.
- Tools: Strong working knowledge of Excel (VLOOKUP, Pivot Tables) and visualization tools (Tableau, PowerBI, or Looker).
- Communication: Excellent verbal and written communication skills with the ability to explain complex data concepts to non-technical audiences.
- Attention to Detail: High level of accuracy and the ability to spot errors in large datasets.