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Assistant Data Scientist Forecasting Jobs in Nebraska

Data Engineer

Omaha, NE · On-site

$109K - $131K/yr

Act as a Subject Matter Expert (SME) to assist in creating practical development plans and ... Bachelor's degree in Computer Science or a related technical field. * Technical Depth: Proven ...

Biological R&D Scientist

Omaha, NE · On-site

$33.75 - $42.25/hr

May assist with necropsy and pathology sampling under senior guidance. Regulatory Contribution ... Strong attention to detail, data integrity, and communication skills; team-oriented * Preferred ...

Biological R&D Scientist

Omaha, NE · On-site

$33.75 - $42.25/hr

May assist with necropsy and pathology sampling under senior guidance. Regulatory Contribution ... Strong attention to detail, data integrity, and communication skills; team-oriented * Preferred ...

Showing results 21-40

Assistant Data Scientist Forecasting information

What are the key skills and qualifications needed to thrive as an assistant data scientist forecasting?

To thrive as an Assistant Data Scientist Forecasting, you need a solid foundation in statistics, data analysis, and forecasting methods, typically supported by a degree in a quantitative field such as mathematics, statistics, or computer science. Familiarity with tools like Python, R, SQL, and forecasting libraries (e.g., Prophet, ARIMA), as well as experience with data visualization platforms, is essential. Strong problem-solving skills, attention to detail, and effective communication help you interpret complex results and present actionable insights. These competencies are crucial to generate accurate forecasts that guide business decisions and drive organizational success.

What does an assistant data scientist forecasting do?

An Assistant Data Scientist in Forecasting helps analyze historical data and uses statistical models or machine learning techniques to predict future trends or outcomes. Their tasks often include data cleaning, exploratory analysis, feature engineering, and supporting the development and validation of forecasting models. They work under the guidance of more experienced data scientists and may also help communicate results to stakeholders. This role is essential for businesses looking to make data-driven decisions about sales, inventory, demand, or other key metrics.

What are some typical challenges assistant data scientists face when working on forecasting projects?

Assistant Data Scientists in forecasting often encounter challenges such as handling incomplete or noisy datasets, selecting appropriate modeling techniques, and tuning models for accuracy. They may also need to balance competing priorities between speed and precision, especially when deadlines are tight. Close collaboration with senior data scientists and domain experts is common, as it helps ensure that forecasts are both technically sound and aligned with business goals. Developing strong communication skills is essential for presenting complex findings to non-technical stakeholders.

What is the difference between Assistant Data Scientist Forecasting vs Data Scientist Forecasting?

AspectAssistant Data Scientist ForecastingData Scientist Forecasting
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles may prefer a master'sMaster's or PhD in Data Science, Statistics, or related field; strong programming skills
Work EnvironmentSupportive team, entry to mid-level projects, supervised tasksIndependent project work, complex analysis, strategic decision-making
Employer & Industry UsageTech companies, finance, retail, healthcare; entry to mid-level rolesResearch institutions, large corporations, specialized analytics teams

The Assistant Data Scientist Forecasting role typically involves supporting forecasting projects under supervision, focusing on data preparation and basic modeling. In contrast, a Data Scientist Forecasting leads complex forecasting models, interprets results, and influences strategic decisions. The roles differ mainly in experience level, scope of responsibilities, and independence.

What are the most commonly searched types of Data Scientist Forecasting jobs in Nebraska? The most popular types of Data Scientist Forecasting jobs in Nebraska are:

Manager of Data Management and Scrum Master

Creighton University

Omaha, NE • On-site

Full-time

Re-posted 16 days ago


Creighton University rating

8.4

Company rating: 8.4 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

97th of 617 rated colleges and universities


Job description

The Manager of Data Management is responsible for leading the day-to-day delivery and operational execution of the University's enterprise data initiatives. Reporting to the Director of Data Management, this role manages a team of data engineers, analysts, developers and database administrators, while serving as Scrum Master to ensure agile delivery of data products and platform capabilities.

This position translates enterprise data strategy into actionable roadmaps, manages the team backlog, facilitates agile ceremonies, and ensures high-quality, secure, and scalable data solutions that support analytics, integration, and institutional decision-making.

The Manager partners closely with data governance, analytics, infrastructure, and campus stakeholders to ensure that data solutions align with institutional priorities and comply with governance and security standards.

Essential Functions:

Team Leadership & Development
    Provide direct supervision and mentorship to data engineers and developers.
    Support career development and skill growth aligned with modern data practices.
    Encourage collaboration, accountability, and agile best practices.
    Assist in hiring, onboarding, and performance management processes.

Agile Delivery & Scrum Leadership
    Serve as Scrum Master for the data management team, facilitating sprint planning, daily stand-ups, retrospectives, and backlog refinement.
    Partner with the Director to translate strategic priorities into deliverable work items and sprint goals.
    Remove blockers and ensure smooth workflow across the team.
    Track delivery metrics and team performance using agile practices.
    Promote continuous improvement and agile maturity within the team.

Platform Operations & Optimization
    Oversee day-to-day health of data platforms, pipelines, and tools.
    Monitor performance and recommend improvements in collaboration with architecture leadership.
    Coordinate with support, organizing bug fixes and incidents for engineers and admins
    Coordinate with Infrastructure & Operations for platform stability and recovery readiness.

Data Platform & Pipeline Delivery
    Lead the implementation of data pipelines, integrations, and platform capabilities.
    Coordinate development of ETL/ELT workflows supporting analytics and operational systems.
    Working with architect, align with enterprise data architecture and governance standards.
    Support deployment, testing, and release management processes.

Data Integration & API Execution
    Manage development and maintenance of system integrations and API implementations.
    Maintain alignment with the University API catalog and integration strategy.
    Ensure data consistency and alignment with governance definitions and business rules.

Data Quality & Operational Governance
    Operationalize data governance standards through implementation practices.
    Monitor data quality processes including validation, cleansing, and monitoring.
    Ensure access provisioning aligns with approved governance workflows.
    Support audit readiness and compliance activities.

Data Governance Implementation:
    Standard Operating Procedure  Development: Collaborate with the University's Analytics and Institutional Reporting (AIR) unit and other applicable groups, to develop and implement data governance policies and procedures that ensure data quality, compliance, and security.
    Compliance Monitoring: Monitor compliance with data governance policies and regulatory requirements, addressing any issues or gaps as needed.

Platform Management:
    Platform Selection: Evaluate and select data management platforms that meet the organization's needs for scalability, performance, and cost-effectiveness.
    Platform Optimization: Continuously optimize data management platforms to ensure they support evolving business requirements and technological advancements.
    Vendor Management: Manage relationships with platform vendors and service providers, ensuring they deliver high-quality products and services.

Team Leadership:
    Team Development: Build and lead a high-performing team of data professionals, providing mentorship, training, and career development opportunities.
    Collaboration: Foster a collaborative and innovative team culture that encourages knowledge sharing and continuous improvement.
    Performance Management: Set performance goals and conduct regular performance reviews to ensure team members meet or exceed expectations.

Stakeholder Collaboration:
    Partner Alignment: Work closely with campus leaders to understand their data needs and ensure data initiatives align with university objectives.
    Cross-Functional Collaboration: Collaborate with IT, AIR, and other departments to deliver integrated data solutions.
    Communication: Communicate data management strategies, progress, and outcomes to partners at all levels of the university.

Qualifications:

    Bachelor's degree in computer science, Information Technology, Data Science, or a related field; Masters degree preferred.
    5-7+ years of experience in data management, with a focus on data architecture, data integration, and database administration.
    Proven experience leading people and creating great work environments
    Proven experience and understanding of agile methodologies with certification preferred.
    Proven experience in leading data initiatives and managing enterprise data lakes.
    Strong experience with API first data strategies

Knowledge, Skills, and Abilities

    Agile methodology and utilization of PPM tools to manage processes
    Ability to professionally articulate the IT vision, goals, and strategy while implementing proactive change in support of strategic goals. 
    Experience facilitating operational planning exercises both internal and external to IT.
    Strong analytical skills
    Ability to cultivate trust and credibility with colleagues, including external constituents. 
    Good understanding of advanced technical components and system interactions
    Expert proficiency in Business case, functional and technical requirement documentation
    Ability to resource plan & manage in a direct reporting and matrixed environment

Soft Skills 
    Strong customer relationship management
    Strong commitment to the mission of Creighton University
    Skilled at giving full attention to what other people are saying, taking time to understand the points being made, asking questions as appropriate, and not interrupting at inappropriate times.
    Ability to communicate effectively and frequently both verbally and in writing.
    Ability to manage and resolve conflicts.
    Knowledge of principles and processes for providing customer and personal services. This includes customer needs assessment, meeting quality standards for services, and evaluation of customer satisfaction.
    Ability to influence multiple stakeholders without direct authority.
    Business acumen coupled with technical knowledge.
    Strong research skills with attention to detail
    Ability to conduct cost/benefit analysis and business case development.
    Must be able to work independently and proactively.
    Excellent organizational, analytical, and independent problem-solving skills 
    Demonstrated understanding of client relationship management, process mapping and improvement, project management, and production support
    Proven ability to provide business analysis for large scope project teams to meet customer expectations. 
    Demonstrated understanding of business analyst tools and techniques; demonstrated proficiency using MS Office and Visio tools

Creighton University is committed to providing a safe and non-discriminatory educational and employment environment. The University admits qualified students, hires qualified employees and accepts patients for treatment without regard to race, color, religion, sex, marital status, national origin, age, disability, citizenship, sexual orientation, gender identity, gender expression, veteran status, or other status protected by law. Its education and employment policies, scholarship and loan programs, and other programs and activities, are administered without unlawful discrimination. Creighton complies with all applicable laws and regulations governing equal opportunity in the workplace and in educational activities.

Applicants with disabilities needing reasonable accommodations to complete the application or hiring process should contact Human Resources at HR@creighton.edu. Creighton University seeks candidates who understand, respect, and can contribute to the University's mission and values. 


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