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Hourly Data Visualization Jobs in Maryland (NOW HIRING)

Droisys

Data Scientist

Fort George G Meade, MD · On-site

The ideal candidate will be responsible for developing and applying probability models, statistical inference, simulations, optimization, data analysis, data visualization, and mathematical models to ...

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Hourly Data Visualization information

What is the difference between Hourly Data Visualization vs Data Analyst?

AspectHourly Data VisualizationData Analyst
CredentialsTypically requires proficiency in visualization tools and basic data skillsRequires degrees in data, statistics, or related fields; often includes certifications
Work EnvironmentProject-based, freelance, or part-time roles often in consulting or agenciesFull-time or part-time roles within organizations, involving data analysis and reporting
Industry UsageUsed across industries for specific visualization tasksCommonly employed for comprehensive data analysis and decision-making

Hourly Data Visualization roles focus on creating visual representations of data on a flexible, often freelance basis, while Data Analysts perform broader data analysis tasks within organizations. Both roles require familiarity with data tools, but Data Analysts typically have more extensive credentials and responsibilities.

What are the most commonly searched types of Data Visualization jobs in Maryland?

The most popular types of Data Visualization jobs in Maryland are:

Hourly Data Visualization jobs near you

Data Scientist 2 with Security Clearance

Innovative Systems & Solutions, Inc.

Annapolis Junction, MD • On-site

Other

Re-posted 14 days ago

Job description

MUST HAVE CURRENT FULL SCOPE POLY
• Programming Languages: Proficiency in programming languages such as Python and R is crucial for data manipulation, analysis, and implementing algorithms. Python is favored for its simplicity and extensive libraries (like NumPy and pandas), while R is preferred for statistical analysis and data visualization. • Statistical Analysis: A strong foundation in statistics and probability is necessary for analyzing data accurately and making informed decisions. Understanding concepts like regression analysis, hypothesis testing, and statistical distributions is essential. • Machine Learning: Knowledge of machine learning algorithms and frameworks (such as TensorFlow and Scikit-Learn) is vital for building predictive models and automating decision-making processes. • Data Wrangling: The ability to clean and organize complex datasets is critical. Data wrangling involves transforming raw data into a usable format, which is often time-consuming but necessary for effective analysis. • Database Management: Familiarity with SQL and database management systems (like PostgreSQL and MongoDB) is essential for extracting and manipulating data stored in relational databases. • Data Visualization: Skills in data visualization tools (such as Tableau and Matplotlib) help communicate findings effectively. Creating charts, graphs, and dashboards is crucial for making data understandable to stakeholders. This position requires in-scope poly, within 7 years.

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