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Data Scientist Data Jobs in Nebraska (NOW HIRING)

Data Scientist Lincoln, Nebraska, USA DESCRIPTION: The Data Scientist may be responsible for any of the following tasks: Analyzing data that is collected in our current and future products and ...

Data Scientist

Omaha, NE · On-site

$107K - $195K/yr

Join Leidos as a Data Scientist and Help Drive Cutting-Edge Analytics Leidos is seeking a forward-thinking Data Scientist with a strong foundation in statistical analysis, data ingestion and ...

Data Scientist

Omaha, NE

$107K - $195K/yr

Join Leidos as a Data Scientist and Help Drive Cutting-Edge Analytics Leidos is seeking a forward-thinking Data Scientist with a strong foundation in statistical analysis, data ingestion and ...

Data Scientist Location: In Person: Falls Church, VA | Ft. Meade, MD | Stuttgart, Baden-Wurttemberg, Germany | Tampa, FL | Honolulu (Camp H.M. Smith), HI | Colorado Springs, CO | Doral (Miami area ...

Data Scientist Clearance: DoD Active Top Secret Location: Omaha, NE Overview: As a Data Scientist at Agile Defense, you will be joining a team of professionals that build AI/ML solutions. This role ...

Data Scientist Clearance: DoD Active Top Secret Location: Omaha, NE Overview: As a Data Scientist at Agile Defense, you will be joining a team of professionals that build AI/ML solutions. This role ...

As a Data Scientist, you will build AI/ML solutions and support business decisions through advanced analytics and predictive modeling. Responsibilities : • Conduct deep-dive analyses to understand ...

They are seeking a Data Scientist to build AI/ML solutions that enhance understanding of customers, markets, and operations through advanced analytics and machine learning, collaborating closely with ...

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Data Scientist Data information

What is the difference between Data Scientist Data vs Data Analyst?

AspectData Scientist DataData Analyst
Required CredentialsDegree in Data Science, Statistics, or related fields; often includes certifications in machine learning or data analysis toolsDegree in Statistics, Mathematics, or related fields; certifications in data visualization or analysis tools are common
Work EnvironmentDevelops predictive models, advanced analytics, and machine learning algorithms; often in R&D or data science teamsPrepares reports, visualizations, and interprets data for business decisions; typically in business intelligence teams
Employer & Industry UsageUsed across tech, finance, healthcare, and e-commerce industries for complex data modelingCommon in retail, marketing, finance, and healthcare for reporting and data interpretation

While both roles analyze data, Data Scientist Data focuses on building predictive models and advanced analytics, whereas Data Analysts primarily interpret data and generate reports for decision-making. The roles often overlap but differ in complexity and scope.

What are some common challenges Data Scientists face when working with large datasets, and how can they be addressed?

Data Scientists often encounter challenges such as data quality issues, scalability concerns, and long processing times when working with large datasets. To address these, it's common to use distributed computing tools like Apache Spark or Hadoop, and to implement efficient data cleaning and preprocessing pipelines. Collaborating closely with data engineers can also help optimize data storage and retrieval. Additionally, adopting best practices in code versioning and documentation ensures that models and analyses are reproducible and scalable as data grows.

What are Data Scientists?

Data Scientists are professionals who analyze and interpret complex digital data to help organizations make informed decisions. They use a combination of statistics, machine learning, programming, and domain expertise to extract insights from large datasets. Data Scientists often work with tools such as Python, R, and SQL, and collaborate with teams to develop predictive models, visualize data, and solve business problems. Their work is crucial in fields like finance, healthcare, technology, and marketing.

What are the key skills and qualifications needed to thrive as a Data Scientist, and why are they important?

To thrive as a Data Scientist, you need strong analytical skills, proficiency in statistics, and experience with data modeling, often supported by a degree in computer science, mathematics, or a related field. Familiarity with programming languages like Python or R, machine learning frameworks, and data visualization tools such as Tableau or Power BI is typically required. Strong problem-solving abilities, effective communication, and curiosity help a Data Scientist translate complex data into actionable insights. These skills are vital for extracting value from data, informing business decisions, and driving innovation within an organization.
What are popular job titles related to Data Scientist Data jobs in Nebraska? For Data Scientist Data jobs in Nebraska, the most frequently searched job titles are:
DATA SCIENTIST

$49K/yr

Other

Posted 22 days ago


Job description

The PALACE Acquire Program offers you a permanent position upon completion of your formal training plan. As a Palace Acquire Intern you will experience both personal and professional growth while dealing effectively and ethically with change, complexity, and problem solving. The program offers a 3-year formal training plan with yearly salary increases. Promotions and salary increases are based upon your successful performance and supervisory approval.Qualifications:BASIC REQUIREMENT OR INDIVIDUAL OCCUPATIONAL REQUIREMENT:
Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
You may qualify if you meet one of the following:
1. GS-7: You must have completed or will complete a 4-year course of study leading to a bachelor's from an accredited institution AND must have documented Superior Academic Achievement (SAA) at the undergraduate level in the following:
a) Grade Point Average 2.95 or higher out of a possible 4.0 as recorded on your official transcript or as computed based on 4 years of education or as computed based on courses completed during the final 2 years of curriculum; OR 3.45 or higher out of a possible 4.0 based on the average of the required courses completed in your major field or the required courses in your major field completed during the final 2 years of your curriculum.
2. GS-9: You must have completed 2 years of progressively higher-level graduate education leading to a master's degree or equivalent graduate degree:
a) Grade Point Average - 2.95 or higher out of a possible 4.0 as recorded on your official transcript or as computed based on 4 years of education or as computed based on courses completed during the final 2 years of curriculum; OR 3.45 or higher out of a possible 4.0 based on the average of the required courses completed in your major field or the required courses in your major field completed during the final 2 years of your curriculum. If more than 10 percent of total undergraduate credit hours are non-graded, i.e. pass/fail, CLEP, CCAF, DANTES, military credit, etc. you cannot qualify based on GPA.
KNOWLEDGE, SKILLS AND ABILITIES (KSAs): Your qualifications will be evaluated on the basis of your level of knowledge, skills, abilities and/or competencies in the following areas:
1. Professional knowledge of basic principles, concepts, and practices of data science to apply scientific methods and techniques to analyze systems, processes, and/or operational problems and procedures.
2. Knowledge of mathematics and analysis to perform minor phases of a larger assignment and prepare reports, documentation, and correspondence to communicate factual and procedural information clearly.
3. Skill in applying basic principles, concepts, and practices of the occupation sufficient to perform routine to difficult but well precedented assignments in data science analysis.
4. Ability to analyze, interpret, and apply data science rules and procedures in a variety of situations and recommend solutions to senior analysts.
5. Ability to analyze problems to identify significant factors, gather pertinent data, and recognize solutions.
6. Ability to plan and organize work and confer with co-workers effectively.
PART-TIME OR UNPAID EXPERIENCE: Credit will be given for appropriate unpaid and or part-time work. You must clearly identify the duties and responsibilities in each position held and the total number of hours per week.
VOLUNTEER WORK EXPERIENCE: Refers to paid and unpaid experience, including volunteer work done through National Service Programs (i.e., Peace Corps, AmeriCorps) and other organizations (e.g., professional; philanthropic; religious; spiritual; community; student and social). Volunteer work helps build critical competencies, knowledge and skills that can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.Education:IF USING EDUCATION TO QUALIFY: If position has a positive degree requirement or education forms the basis for qualifications, you MUST submit transcriptswith the application. Official transcripts are not required at the time of application; however, if position has a positive degree requirement, qualifying based on education alone or in combination with experience, transcripts must be verified prior to appointment. An accrediting institution recognized by the U.S. Department of Education must accredit education. Click here to check accreditation.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying.Employment Type: OTHER