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Marketing Data Analyst Resume Examples

Marketing Data Analysts use market data collected by professionals to help companies make informed decisions when it comes to marketing their products and services. Duties of experienced Marketing Data Analysts include performing qualitative and quantitative analysis, interpreting findings, helping managers to understand market data, graphing marketing data, and using predictive modeling to make forecasts. Resume samples in the field highlight skills such as marketing expertise, statistics knowledge, effective communication, organizational skills, computer competences, and decision-making. Employers choose resumes showcasing a degree in marketing or a similar field.

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Data Analyst Duties and Responsibilities

Data analysts take on a range of duties depending on the organization they work for. Based on job listings we analyzed, a data analyst's duties typically involve:

Interpreting Data Using statistical techniques, data analysts analyze results from data, using this information to create ongoing reports.

Implementing Databases Data analysts develop and implement databases, as well as data analytics and strategies to optimize the efficiency and quality of data processes within the organization.

Gathering Information from Other Sources A key part of this job is to acquire data from primary and secondary sources, to use to maintain data systems.

Identifying Trends Data analysts look at the data they've collected to find patterns or trends in complex data sets. This also helps in cleaning data by reviewing computer reports and performance indicators to correct any coding problems.

Finding Ways to Improve Processes Data analysts work with management to establish the company's business goals and information needs so that these can be prioritized. They also define new processes and ways to improve on how information is gathered and used.

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Data Analyst Skills and Qualifications

Data analysts should have strong numerical abilities, be critical thinkers, and be able to communicate complex information in an easy-to-follow way that people with no data knowledge can comprehend. Typically, employers require a bachelor's degree in mathematics, computer science, or a similar field, as well as the following abilities:
  • Analytical skills - data analysts interpret and analyze data to draw conclusions and identify patterns
  • Computer knowledge - this position uses statistical and analytical software
  • Communication skills - data analysts often have to present their findings or translate the information into an easy-to-understand document, so the ability to communicate complex data, and to write and speak clearly, are important
  • Math skills - data analysts need to have strong numeracy skills to estimate and interpret numerical data
  • Attention to detail - it's vital that data analysts be precise in their work, able to spot errors, and vigilant to ensure that any problems are corrected for accurate results
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Data Analyst Education and Training

The minimum requirement to become a data analyst is a bachelor's degree in mathematics, statistics, computer science, or a similar subject. For upper-level positions, a master's degree in these areas is beneficial. Data analysts have to have experience in analysis and math, and depending on the area of specialization, certification can also be required.
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Data Analyst Salary and Outlook

The median annual salary for data analysts is $58,000, according to PayScale. Data analysts in the 10th percentile earn around $41,000 annually, while the highest paid earn close to $82,000 a year. Some companies offer packages that can reach up to $9,000 from bonus structures based on individual or group performances, and the same in profit sharing opportunities. Seventy-five percent of employers offer dental plans and 85 percent offer medical insurance as part of their benefits package.
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Helpful Resources

We've collected some of the best resources to help you learn how to develop a career as a data analyst:

Data Scientist and Analysts - This LinkedIn group has over 4,300 members, all related to the data science and analysis industry. For those new to this sector, networking with like-minded people and finding a new source of knowledge is useful for developing a better understanding of tips and techniques that can be used day to day.

Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking - A great guide for learning the fundamental principles of data science and analysis, this book walks readers through the ‘data analytical thinking' needed for providing business value to data. It covers the main data-mining techniques needed for this position, as well as how to treat data as a business asset, approaching business problems analytically, and understanding how data science fits into businesses.

Practical and Efficient SAS Programming: The Insider's Guide - SAS is a flexible program, but it can look complex to those unfamiliar with it. This book provides general SAS programming tips and tools that can be utilized in the workplace. Including self-contained sections that describe each technique with numerous examples, it's easy to follow and ideal for SAS programming novices.

Analytics Vidhya - This blog, run by Kunal Jain, focuses on building a community that revolves around the topic of analytics study. From knowledge sharing and tips to networking with others in the industry, it's a useful blog to help develop knowledge.

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