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Data Analyst Data Science Jobs in Iowa (NOW HIRING)

Data Scientist 1

Des Moines, IA ยท On-site +1

$81K - $124K/yr

One year of full-time work experience in business/data/statistical analytics, economic research, or data science; and b. A total of four years of education and/or full-time experience (as described ...

Lead Data Engineer

Cedar Rapids, IA ยท On-site

$112K - $134K/yr

Work collaboratively with other engineers, data scientists, analytics teams, and business product owners in an agile environment: * Architect, build, and support the operation of Cloud and On ...

Lead Data Engineer

Cedar Rapids, IA

$112K - $134K/yr

Work collaboratively with other engineers, data scientists, analytics teams, and business product owners in an agile environment: * Architect, build, and support the operation of Cloud and On ...

LCS is looking for a visionary VP of Data & AI to lead the organization's transformation to becoming AI-native, spanning data analytics, data science, data governance, and AI. This leader is ...

LCS is looking for a visionary VP of Data & AI to lead the organization's transformation to becoming AI-native, spanning data analytics, data science, data governance, and AI. This leader is ...

LCS is looking for a visionary VP of Data & AI to lead the organization's transformation to becoming AI-native, spanning data analytics, data science, data governance, and AI. This leader is ...

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Data Analyst Data Science information

See Iowa salary details

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How much do data analyst data science jobs pay per hour?

As of Jun 22, 2026, the average hourly pay for data analyst data science in Iowa is $37.93, according to ZipRecruiter salary data. Most workers in this role earn between $27.36 and $45.96 per hour, depending on experience, location, and employer.

Is 40 too late for data science?

Data analysts and data scientists can start their careers at any age, including 40 or older. Success in data science depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, which can be learned at any stage of life. Many professionals transition into data roles later in their careers with dedication and continuous learning.

How do Data Analysts in Data Science typically collaborate with other departments or teams?

Data Analysts in Data Science frequently work cross-functionally, partnering with teams such as engineering, product management, marketing, and business intelligence. They translate complex data findings into actionable insights and tailor their communication to both technical and non-technical stakeholders. Regular collaboration may involve participating in meetings to understand business needs, designing dashboards for different teams, and providing data-driven recommendations to support company objectives. This collaborative environment not only enhances project outcomes but also fosters continuous learning and professional growth.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of the results come from 20% of the efforts or data. Data analysts often use this concept to focus on the most impactful variables or features during analysis and modeling to improve efficiency and accuracy.

What does a Data Analyst in Data Science do?

A Data Analyst in Data Science collects, processes, and analyzes large sets of data to help organizations make informed decisions. They use statistical techniques and data visualization tools to identify trends, patterns, and insights from data. Their responsibilities often include cleaning data, creating reports, and communicating findings to stakeholders. Data Analysts play a key role in helping businesses optimize operations, understand customer behavior, and solve complex problems using data-driven approaches.

Can data science work as a data analyst?

Data science and data analysis are related fields, but they have different focuses. Data scientists often develop models and algorithms using programming languages like Python or R, while data analysts primarily interpret data, generate reports, and use tools like Excel or SQL. Skills in statistical analysis, data visualization, and understanding business needs are essential for both roles, and some professionals transition between them based on experience and training.

What is the difference between Data Analyst Data Science vs Data Engineer?

AspectData Analyst Data ScienceData Engineer
Required SkillsStatistics, programming (Python, R), data visualizationDatabase systems, ETL pipelines, programming (Python, Java)
Work EnvironmentAnalyzing data, building models, reportingBuilding and maintaining data infrastructure
CertificationsData Science certifications, SQL, PythonCloud certifications, database management
Industry UsageBusiness analysis, predictive modelingData infrastructure, big data systems

Data Analyst Data Science focuses on analyzing data and creating models to inform decisions, while Data Engineers build the systems that collect, store, and process data. Both roles require programming skills and often overlap in tools like Python and SQL, but their core responsibilities differ significantly.

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

To thrive as a Data Analyst in Data Science, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Familiarity with tools like SQL, Python or R, and data visualization platforms such as Tableau or Power BI, along with industry-recognized certifications, is highly valued. Attention to detail, problem-solving abilities, and effective communication skills help you interpret data insights and convey findings to stakeholders. These skills are crucial for transforming raw data into actionable intelligence that drives strategic business decisions.

Is AI replacing data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, allowing analysts to focus on more complex insights and strategic decision-making. While AI tools can augment their work, human expertise remains essential for interpreting results, understanding context, and communicating findings effectively. Data analysts who develop skills in machine learning, programming, and data visualization will continue to be valuable in the evolving data science environment.
What are popular job titles related to Data Analyst Data Science jobs in Iowa? For Data Analyst Data Science jobs in Iowa, the most frequently searched job titles are:
What job categories do people searching Data Analyst Data Science jobs in Iowa look for? The top searched job categories for Data Analyst Data Science jobs in Iowa are:
What cities in Iowa are hiring for Data Analyst Data Science jobs? Cities in Iowa with the most Data Analyst Data Science job openings:
Data Analysis and Reporting Manager

Data Analysis and Reporting Manager

Practical Farmers of Iowa

Ames, IA โ€ข On-site

Full-time

Medical, Retirement, PTO

Posted 4 days ago


Job description

Description:

Practical Farmers of Iowa is Hiring a Data Analysis and Reporting Manager


About PFI

Practical Farmers of Iowa is a nonprofit organization that has worked to equip farmers to build resilient farms and communities since 1985. We create learning opportunities via farmer-led events, on-farm research and educational content through our robust network of farmers. We also provide funding and technical assistance to help farmers adopt regenerative farming practices and grow farm businesses. Our vision is an Iowa with healthy soil, healthy food, clean air, clean water, resilient farms and vibrant communities.


This work has always been rooted in our value of welcoming everyone and creating a culture of mutual respect. We believe that a diversity of people, ideas and perspectives strengthens our ability to find creative solutions, enriches our understanding and broadens our impact. At Practical Farmers, we celebrate this diversity and are committed to ensuring that our policies and practices create an equitable and inclusive workplace. We take equal opportunity seriously and seek to empower and support all applicants and teammates.


Practical Farmers offers a flexible, supportive and fast-paced work environment. Professional development is a core part of our culture and team members are encouraged to take independent initiative to help fulfill our mission.


About the Position

The data analysis and reporting manager will lead the development and implementation of systems that transform farm-level production and geospatial data into trusted sustainability outcomes. This position sits within Practical Farmersโ€™ farm viability department and plays a critical role in supporting farmer participation in emerging environmental markets and sustainability initiatives.


The data analysis and reporting manager will oversee data collection, stewardship, quality assurance, modeling and reporting processes that support greenhouse gas accounting, sustainability reporting and program evaluation. Working across agronomy, data, science and external partner teams, this role will ensure data integrity, audit readiness and continuous improvement of Practical Farmersโ€™ monitoring and reporting systems.


The ideal candidate combines expertise in agricultural production systems, data management, geospatial information and sustainability analytics with strong project management and communication skills. They will help build scalable systems that enable Practical Farmers to deliver credible, science-based outcomes for farmers, supply chain partners and other stakeholders while advancing PFIโ€™s mission of supporting resilient farms and communities.


Duties

  • Manage data stewardship and reporting projects.
  • Working with PFI staff and contractors, manage the collection of farm production data (inputs, yields, practices, management systems).
  • Oversee geospatial data ingestion (geospatial information systems layers, field boundaries, remote sensing inputs),?including supervising contractors.
  • Coordinate data pipelines across agronomy, field teams and external partners.
  • Ensure consistency, completeness and traceability of all monitoring, reporting and verification input datasets.
  • Analyze data stewardship and reporting data and report results.
  • Run and manage outputs using tools such as Fieldprint-style calculators and carbon modeling platforms like Roth C or other models using R-code or other packages.
  • Translate agronomic and geospatial data into greenhouse gas estimates and sustainability metrics.
  • Support Scope 1, 2 and 3 inventory development through structured data inputs.
  • Collaborate with sustainability and science teams to refine emission factors and methodologies.
  • Design and implement processes to ensure consistency and efficiency of data stewardship and reporting subdepartment.
  • Maintain monitoring, reporting and verification data systems for audit readiness and third-party verification.
  • Support development of an annual greenhouse gas inventory and science-based targets for initiative tracking requirements.
  • Ensure documentation of methodologies, assumptions and data lineage.
  • Strengthen quality assurance and quality control protocols across all monitoring, reporting and verification datasets.
  • Facilitate collaboration between departments and teams to achieve data stewardship and reporting project goals.
  • Work closely with data architecture and engineering teams to optimize data flows.
  • Support integration of geospatial information systems (e.g., ESRI), databases and reporting tools.
  • Contribute to the development of a centralized emissions and sustainability data warehouse.
  • Improve automation between field data capture, modeling tools and reporting outputs.
  • Partner with agronomy teams to interpret field practices into data models.
  • Develop and manage partnerships related to data stewardship and reporting that leverage both organizations' work toward PFI's goals.
  • Collaborate with sustainability reporting teams on disclosures and frameworks (Greenhouse Gas Protocol, Task Force on Climate-Related Financial Disclosures, etc.).
  • Support supplier engagement efforts to improve upstream data quality and emissions factors.
  • Provide analytical support for lifecycle assessments and scenario modeling.
  • Other duties as assigned or volunteered to support department or team projects.


Required Qualifications and Characteristics

  • A masterโ€™s degree in a science field
  • Experience with measurement, reporting and verification systems and audit requirements
  • Familiarity with agricultural production systems and farm management practices (inputs, yields, soil practices, etc.)
  • Knowledge of geospatial data systems (GIS concepts, field boundaries, remote sensing basics)
  • Understanding of data governance, quality assurance and quality control standards and traceability requirements for reporting
  • Experience building and managing structured datasets combining farm production and geospatial data
  • An ability to analyze large, complex datasets and translate them into emissions and sustainability metrics
  • Experience working with data tools such as Excel, structured query language, Power BI and geospatial information systems platforms (e.g., ESRI)
  • The ability to collaborate to design and improve data workflows and reporting pipelines across teams
  • Familiarity with conducting quality assurance and quality control on emissions inventories to ensure audit readiness
  • The ability to communicate technical data clearly to agronomy, sustainability and leadership teams
  • Strong interpersonal communication skills (written and verbal)
  • An ability to connect field-level agricultural data to enterprise emissions reporting systems
  • An ability to interpret incomplete or imperfect datasets and still produce reliable outputs
  • The ability to maintain high attention to detail in high-stakes reporting environments
  • Skill identifying gaps in data systems and proactively designing improvements
  • The ability to prioritize multiple reporting cycles, deadlines and stakeholder needs simultaneously

Desired Qualifications and Characteristics

  • A doctorate in a science field
  • Experience with the Greenhouse Gas Protocol (Scopes 1, 2 and 3) and agricultural emissions accounting
  • Knowledge of lifecycle assessment (LCA) principles and carbon accounting methodologies
  • Experience with sustainability disclosure frameworks (science-based targets initiative, carbon disclosure project, international sustainability standards board, international organization for standardization standards)
  • Experience operating or coordinating emissions modeling tools (e.g.,Fieldprint-style calculators, lifetime cycle assessment tools)
  • Experience collaborating with data engineers and architects to improve system integration and automation
  • The ability to manage cross-functional coordination across agronomy, data and sustainability teams
  • The ability to translate technical monitoring, reporting and verification outputs into business insights and decisions


This is a full-time position with potential for hybrid work. There is a minimum requirement of one day per month at the Ames, Iowa, office and seasonal travel around Iowa and surrounding states. The beginning salary range for this position is $58,000-$62,000 with annual opportunity for salary increases and position advancement.


PFI values its employees and is a flexible and supportive work environment. We offer employees a competitive benefits package that includes employee health insurance with 100% employer-paid premium, generous paid time off, flexible hours, six weeks of fully paid parental leave and 5% automatic 401k contribution after one year of employment.


We also encourage employee professional development and offer a range of specialty benefits employees can use to support their wellness, sustainability and financial goals. Examples of our specialty benefits include contributions towards spouse or dependent health insurance, stipends for remote workers and reimbursements for fitness costs, CSA subscriptions, student loans or eco-friendly purchases. Practical Farmers is a family-friendly employer.


Please apply by completing an application (including contact information, cover letter, resume and references). Applications will be reviewed on a rolling basis.

Requirements: