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Director Data Science Startup Jobs in Nebraska (NOW HIRING)

ACT Science Tutor

Omaha, NE · Remote

$18 - $40/hr

Emphasizes minimal passage reading, direct data analysis, and recognizing question patterns for maximum efficiency. * Test Strategy & Adaptive Instruction: Familiar with ACT Science time pressure ...

ACT Science Tutor

Lincoln, NE · Remote

$18 - $40/hr

Emphasizes minimal passage reading, direct data analysis, and recognizing question patterns for maximum efficiency. * Test Strategy & Adaptive Instruction: Familiar with ACT Science time pressure ...

Ability to work effectively across business and technology teams without direct authority. * Strong ... Bachelor's degree in Data Science, Computer Science, Statistics, Engineering, or a related field ...

Required : • A bachelor's degree or higher in Data Science, Computer Science, Data Analytics ... • Direct experience developing Machine Learning models required. • Active TS/SCI clearance ...

Bachelor's degree in Computer Science, Engineering, Business or a related field (preferred, not ... Strong analytical and critical thinking abilities, with a data-driven approach to decision-making

Bachelor's degree in Computer Science, Engineering, Business or a related field (preferred, not ... Strong analytical and critical thinking abilities, with a data-driven approach to decision-making

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Director Data Science Startup information

What are some unique challenges a Director of Data Science faces in a startup environment?

As a Director of Data Science in a startup, you will often need to balance hands-on technical work with strategic leadership, since resources and team sizes are usually limited. You'll likely be tasked with building and mentoring a team from the ground up, establishing best practices, and aligning data initiatives with fast-changing business goals. Additionally, you may need to advocate for data-driven decision-making across non-technical teams and adapt quickly as the company's priorities shift. This environment fosters rapid professional growth but requires flexibility, strong communication skills, and a willingness to wear multiple hats.

What is the difference between Director Data Science Startup vs Data Scientist?

AspectDirector Data Science StartupData Scientist
Required CredentialsAdvanced degree (Master's/PhD), leadership experienceBachelor's or Master's in Data Science, Computer Science, or related field
Work EnvironmentLeadership role overseeing teams, strategic planningHands-on data analysis, model development, research
Employer & Industry UsageStartups, tech companies, innovation-driven firmsVaries from startups to large corporations, research labs
Search & Comparison IntentUnderstanding leadership roles, strategic responsibilitiesTechnical skills, project work, data analysis

The Director Data Science Startup typically holds a leadership position with strategic oversight and team management responsibilities, requiring advanced degrees and experience. In contrast, a Data Scientist focuses on technical data analysis and model development, often with less emphasis on leadership. Both roles are common in startup environments and tech industries, but they differ significantly in scope and responsibilities.

What are the key skills and qualifications needed to thrive as a Director of Data Science at a Startup, and why are they important?

To thrive as a Director of Data Science at a startup, you need deep expertise in statistical modeling, machine learning, and data strategy, often supported by an advanced degree in a quantitative field. Familiarity with tools like Python, R, SQL, cloud platforms (e.g., AWS, GCP), and experience with data pipeline architectures are typically required. Strong leadership, communication, and business acumen are vital soft skills for aligning data initiatives with startup objectives and motivating cross-functional teams. These skills are crucial for driving product innovation, scaling data operations, and delivering actionable insights in a fast-paced, resource-constrained environment.

What does a Director of Data Science do at a startup?

A Director of Data Science at a startup leads the development and execution of data-driven strategies, overseeing teams of data scientists and analysts to drive business growth. They are responsible for aligning data initiatives with the company's goals, building predictive models, and ensuring the integrity and scalability of data solutions. This role often involves close collaboration with engineering, product, and executive teams to translate business needs into actionable data projects. Additionally, they help shape the data culture and mentor team members in a fast-paced, resource-constrained environment.
What are the most commonly searched types of Data Science Startup jobs in Nebraska? The most popular types of Data Science Startup jobs in Nebraska are:
What are popular job titles related to Director Data Science Startup jobs in Nebraska? For Director Data Science Startup jobs in Nebraska, the most frequently searched job titles are:
What cities in Nebraska are hiring for Director Data Science Startup jobs? Cities in Nebraska with the most Director Data Science Startup job openings:

Mathematical Statistician (Data Scientist) - Direct Hire

Criminal Investigation & Law Enforcement | IRS Careers

Norfolk, NE

$74K/yr

Other

Posted 11 days ago


Job description

WHAT IS DATA AND ANALYTICS?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO- Data and Analytics Office (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
IOR BASIC REQUIREMENTS GS-1529 Mathematical Statistician (Data Scientist):
You must have a degree that included courses in mathematics and statistics totaling at least 24 semester hours. This course work must have included a minimum of 12 semester hours of mathematics, and 6 semester hours were in statistics. Courses acceptable toward meeting the mathematics course requirement must have included at least four of the following: differential calculus, integral calculus, advanced calculus, theory of equations, vector analysis, advanced algebra, linear algebra, mathematical logic, differential equations, or any other advanced course in mathematics for which one of these was a prerequisite. Courses in mathematical statistics or probability theory with a prerequisite of elementary calculus or more advanced courses will be accepted toward meeting the mathematics requirements, with the provision that the same course cannot be counted toward both the mathematics and the statistics requirement.
OR
Combination of education and experience -- includes at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as described above; and Experience that showed evidence of statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying known statistical techniques to data such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
GS-1529-11 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science projects.
  2. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  3. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  4. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  5. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  6. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
OR
EDUCATION: You may substitute education for specialized experience specialized experience as follows: Three (3) full academic years of progressively higher-level graduate education in Mathematics, statistics, or related fields.
OR
Ph. D. or equivalent doctoral degree Mathematics, statistics, or related field of study from an accredited college or university.
OR
Combination of education and experience: A combination of qualifying graduate education and experience equivalent to the amount required.
GS-1529-12 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience applying knowledge of statistical theories, principles, concepts and practices that relate to experimental design, data analysis, sampling, forecasting, quality control, and operations research to understand, model and improve program operations.
  2. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  3. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  4. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  5. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  6. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  7. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.

GS-1529-13 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service.
Examples of specialized experience for this position may include:
  1. Experience applying project management principles on a data science project.
  2. Experience planning and executing a variety of data science and/or analytics projects.
  3. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  4. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  5. Experience working with multiple data types and formats as a part of a data science project.
  6. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  7. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  8. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  9. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
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. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER