Entry Level Junior Data Analyst Jobs | OPTnation

No matter the level of experience, all data analysts have the same objective: to explore data and produce insights that can be used to advance a business. However, in general, in entry level data analyst jobs individuals are expected to perform more "basic" duties. Despite how crucial these jobs are, they frequently function independently inside the larger data analytics process. Entry-level data analysts support individuals with more expertise through their work by performing many of the same responsibilities. While a junior data analyst in such IT jobs may do many of the same duties as a senior analyst, the intricacy and importance of their duties will be far lower.

Job prospects for data analysts

The future is really bright for data analysts in terms of employment: The US Bureau of Labour Statistics (BLS) projects that between 2021 and 2031, there will be a 23 percent increase in the number of job openings for operations research analysts, which is the profession that includes data analysts. The BLS forecasts that over that time, there would, on average, be 10,300 new job vacancies each year.

What types of fields are entry-level data analysts employed in?

What sectors can entry-level data analysts work in now that we know what they do in general? The good news in this situation is that almost all of the sectors you can imagine employ young data analysts. Data permeates every facet of our lives, especially those that include the internet, and industries as diverse as finance and retail are making use of the predictive value of these data.

Read More: Best Paying Data Analyst Jobs in USA in 2023-2024

However, data analytics is notably active in the following sectors of the economy. Any of these is a terrific place to start if you're looking for an entry-level position:

• Insurance: Risk analysis is an essential ability in the insurance industry. As a result, businesses are always looking for talented analysts.

• Finance: Data analytics is used in the world of finance for things like product creation and sales tactics. Additionally, fraud detection uses it.

• Financial reporting and advisory services: The biggest accounting companies in the world make it their business to change how their clients do business. For entry-level data analyst positions, they specifically headhunt graduates because the nature of their work necessitates very specialised training. There is also a tonne of career advancement available.

• Healthcare: Data analysts in the healthcare industry use pharmacological data and electronic medical records to enhance patient outcomes. Moreover, they apply it to product design.

• High tech: Among of the most well-known supporters of data analytics are the huge IT businesses that we are all familiar with. The companies that operate in an ever-wider range of industries, including Google, Apple, Microsoft, and Amazon, are continually looking for entry-level data analysts who they can train to work in those industries.

Alternatively, for your job search, you can look up OPTnation to find such jobs.

Job Title: Entry level junior data analyst.

Location: USA

Job Type: Full-Time, Part-Time, Contract, Training

Salary: $11000 - $12000 per year

Industry: Information Technology

Responsibilities:

• Does statistical analysis for internal customer groups and gathers, combines, and analyses data from multiple databases.

• Develops dashboards and/or reports to provide the financial data necessary for company decision-making.

• Designs, develops, and employs templates for data collection, visualisation, and analysis for specified projects.

• Explains complicated information in ways that are understandable. evaluates data from several sources and expresses the final analysis's quality clearly.

• Creates reports and other tools to provide corporate data to business users, enabling them to make educated decisions.

• Collects data about firm finances from various outside sources, models it, and then analyses it.

Skills:

• Data preparation and cleansing.

• Data exploration and analysis.

• Statistical expertise.

• Visualisation of data.

• Making reports and dashboards.

• Writing and speaking.

• Domain expertise.

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