Data Analyst/ Health Data Analyst Job at 22nd Century Technologies in Richmond

Title: Data Analyst/ Health Data Analyst

Location: Richmond, VA 23219(Hybrid)

Pay Rate: $25.00/Hour on W2 without benefits.

Duration: 2.5 Yrs.

Shift Timing (Day/ Evening/ Night): Day

Job Description:

Equipment to be used by the temporary staffing professional(s):

• VDH Provided mobile phone, laptop and printer

Computer software to be used:

• MS Teams, Microsoft Office Suite

Desired skills:

• Statistical Methods and Techniques: Understanding of statistical concepts, such as regression analysis, hypothesis testing, probability distributions, and data sampling techniques.
• Data Management and Databases: Experience working with databases, data manipulation, and querying using SQL or other database management tools. Familiarity with relational and non-relational databases (e.g., MySQL, PostgreSQL, MongoDB).
• Data Cleaning and Transformation: Knowledge of data wrangling techniques to clean and preprocess data, identify inconsistencies, and prepare data for analysis.
• Data Visualization: Ability to present findings through data visualization techniques, using tools like Tableau, Power BI, or custom dashboards, to make complex data insights easily understandable.
• Problem-Solving and Critical Thinking: Ability to interpret data trends and draw actionable insights that can inform business decisions and strategies.
• Data Interpretation and Reporting: Ability to summarize complex data findings and present them clearly to non-technical stakeholders, including managers and executives.

Knowledge, skills, education, and/or experience:

• Having a strong educational foundation in analytics or a related field, combined with technical skills and industry knowledge, is key to a successful career as a data analyst.

Role & Responsibilities:

Data Analysis:

• Analyze large datasets to identify trends, patterns, and insights that can inform business decisions.
• Apply statistical techniques to analyze data, interpret findings, and make data-driven recommendations.
• Develop and apply models for predictive analysis, forecasting, or risk assessment (if applicable).
• Data Reporting and Visualization:
• Create clear, actionable, and visually appealing reports and dashboards to communicate findings to stakeholders.
• Use data visualization tools (e.g., Tableau, Power BI) to present data insights in a user-friendly manner.
• Prepare presentations summarizing complex data findings for non-technical audiences.

Data Analysis:

• Analyze large datasets to identify trends, patterns, and insights that can inform business decisions.
• Apply statistical techniques to analyze data, interpret findings, and make data-driven recommendations.
• Develop and apply models for predictive analysis, forecasting, or risk assessment (if applicable).
• Data Reporting and Visualization:
• Create clear, actionable, and visually appealing reports and dashboards to communicate findings to stakeholders.
• Use data visualization tools (e.g., Tableau, Power BI) to present data insights in a user-friendly manner.
• Prepare presentations summarizing complex data findings for non-technical audiences.
• Collaboration and Stakeholder Interaction:
• Work closely with internal teams to understand data needs and business goals.
• Communicate insights, trends, and recommendations to stakeholders to inform strategic decision-making.
• Provide support and guidance on data-related matters across various departments.
• Data Interpretation and Insights:
• Translate complex data into actionable insights that can influence business strategies, improve processes, or optimize performance.
• Identify key performance indicators and ensure they are tracked consistently to measure business outcomes.
• Data Quality Assurance:
• Conduct routine checks for data quality, identify discrepancies, and implement processes for data correction.
• Ensure data privacy and compliance with applicable regulations (e.g., GDPR, HIPAA) when handling sensitive information.
• Reporting and Documentation:
• Create and maintain detailed documentation of data analysis processes, methodologies, and models used.
• Prepare periodic reports on data trends, forecasts, and analyses for management or clients.
• Continuous Improvement:
• Identify opportunities to automate data collection and reporting processes to improve efficiency.
• Suggest improvements to data collection methodologies and business processes based on data-driven insights.