Data Analyst

Roles and responsibilities

We are looking for a passionate certified Data Analyst. The successful candidate will turn data into information, information into insight and insight into business decisions.

Data analyst responsibilities include conducting full lifecycle analysis to include requirements, activities and design. Data analysts will develop analysis and reporting capabilities. They will also monitor performance and quality control plans to identify improvements.

Responsibilities

• Interpret data, analyze results using statistical techniques and provide ongoing reports
• Develop and implement databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality
• Acquire data from primary or secondary data sources and maintain databases/data systems
• Identify, analyze, and interpret trends or patterns in complex data sets
• Filter and “clean” data by reviewing computer reports, printouts, and performance indicators to locate and correct code problems
• Work with management to prioritize business and information needs
• Locate and define new process improvement opportunities
  

Requirements

• Proven working experience as a data analyst or business data analyst
• Technical expertise regarding data models, database design development, data mining and segmentation techniques
• Strong knowledge of and experience with reporting packages (Business Objects etc. ), databases (SQL etc.), programming (XML, Java script, or ETL frameworks)
• Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS etc.)
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
• Adept at queries, report writing and presenting findings
• BS in Mathematics, Economics, Computer Science, Information Management or Statistics

Desired candidate profile

• Analytical Skills: Ability to interpret complex data sets and identify trends, patterns, and insights.

• Technical Proficiency: Proficiency in data analysis tools and software, such as Excel, SQL, Python, R, or Tableau.

• Statistical Knowledge: Understanding of statistical methods and techniques for data analysis and validation.

• Data Visualization: Skill in creating clear and compelling visual representations of data to communicate findings effectively.

• Attention to Detail: Ensuring accuracy in data collection, analysis, and reporting to avoid errors.

• Problem-Solving Skills: Ability to approach data challenges creatively and develop actionable solutions.

• Communication Skills: Strong verbal and written communication to present data findings to non-technical stakeholders.

• Critical Thinking: Evaluating data critically to draw meaningful conclusions and make informed recommendations.

• Database Management: Familiarity with database systems and data warehousing concepts.

• Project Management: Ability to manage multiple projects, prioritize tasks, and meet deadlines efficiently.