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Data Analyst Data Science Jobs in Springfield, MO

Danaher

Digital Analyst Internships

Springfield, MO · On-site

$89K - $106K/yr

Students currently pursuing a bachelor's degree in Computer Science, Information Systems, or a related field * Familiarity with data analysis platforms and tools, comfortable extracting and ...

Brightli

Principal AI Engineer

Springfield, MO

Bachelor's degree or equivalent experience in Computer Science, Data Engineering, Data Science, Information Systems, or related field 7+ years of experience in data, analytics, engineering, or ...

SynergisticIT

Business Analyst

Springfield, MO

Excellent written and verbal communication skills Required Skills for Data Science/Machine Learning ... Databricks, Snowflake, Text mining, Tableau, PowerBI, Time series analysis Please understand skills ...

Brightli

Principal AI Engineer

Springfield, MO · On-site

... Data Engineering, Data Science, Information Systems, or related field. • 7+ years of experience in data, analytics, engineering, or applied AI roles. • Demonstrated experience building or ...

Brightli

Principal AI Engineer

Springfield, MO · On-site

... Data Engineering, Data Science, Information Systems, or related field • 7+ years of experience in data, analytics, engineering, or applied AI roles • Demonstrated experience building or ...

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Data Analyst Data Science information

See Springfield, MO salary details

$30.9K

$75.2K

$123.7K

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

As of Jun 18, 2026, the average yearly pay for data analyst data science in Springfield, MO is $75,172.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,900.00 and $88,200.00 per year, 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 Springfield, MO? For Data Analyst Data Science jobs in Springfield, MO, the most frequently searched job titles are:
What job categories do people searching Data Analyst Data Science jobs in Springfield, MO look for? The top searched job categories for Data Analyst Data Science jobs in Springfield, MO are:
What cities near Springfield, MO are hiring for Data Analyst Data Science jobs? Cities near Springfield, MO with the most Data Analyst Data Science job openings:
Data Analyst Data Science jobs near you
Infographic showing various Data Analyst Data Science job openings in Springfield, MO as of June 2026, with employment types broken down into 1% As Needed, 70% Full Time, 22% Part Time, and 7% Contract. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $75,172 per year, or $36.1 per hour.

Business Data Analyst (Fixed-Term Contract)

CREATIVE MODULAR CONSTRUCTION LLC

Springfield, MO • On-site

Full-time, Contractor

Posted 16 days ago

Job description

Job Title: Business Data Analyst (Fixed-Term Contract)
Location: Springfield, MO
Pay: Competitive compensation based on experience
Job Type:
• Full-Time Fixed-Term Contract
• Six-Month Contract Position
Join Our Team at Creative Modular Construction (CMC)
CMC is seeking a Business Data Analyst for a six-month fixed-term contract to turn enterprise data into trusted, decision-ready information across our Epicor ERP and ADP HRIS platforms. This role designs and maintains reports, dashboards, and datasets that Finance, Operations, Project Management, and Human Resources rely on, while ensuring that the metrics behind them are consistent, accurate, and well-documented.
Reporting to the ERP Business Analyst and working alongside a peer Business Data Analyst focused on field service data, this role provides additional analytical capacity across core ERP and HRIS reporting domains during a period of peak demand. The Business Data Analyst will partner closely with stakeholders across the organization to answer the questions that drive business decisions.
What You'll Do
• Design, build, and maintain reports, dashboards, and self-service datasets across Epicor ERP and ADP HRIS
• Develop and document metric and KPI definitions to ensure a single, agreed meaning for each measure
• Build reusable query layers, including Epicor BAQs and equivalent ADP extracts, that business users can safely leverage
• Partner with the ERP Business Analyst to translate business questions into analytical specifications and validate reporting requirements
• Establish and execute data quality checks and reconciliation routines for ERP and HRIS reporting deliverables
• Lead analyses across finance, operations, project, and workforce data, including trend analysis, variance investigation, and cross-platform reconciliation
• Present analytical findings and recommendations to business stakeholders
• Support period-end and audit cycles through reliable, traceable data extracts and reconciliations
• Coordinate with the FSM-focused Business Data Analyst to ensure consistent definitions and shared data assets across teams
• Identify opportunities to automate recurring reporting and reduce manual data handling
• Maintain reporting documentation, metric definitions, and report inventories
• Provide reporting coverage for the FSM domain when needed
• Contribute to data governance initiatives and continuous improvement efforts
• Perform other duties as assigned
What We're Looking For
• Bachelor's degree in Information Systems, Statistics, Finance, Business, Computer Science, or a related field; equivalent experience considered
• Three or more years of data analysis or business intelligence experience, including reporting against an ERP or HRIS platform
• Strong SQL skills and solid dimensional/data-modeling experience
• Proficiency with Power BI or similar business intelligence and visualization tools
• Experience with Epicor BAQs, dashboards, or comparable ERP reporting tools
• Advanced spreadsheet skills
• Strong analytical thinking and attention to detail
• Ability to communicate complex findings clearly to both technical and non-technical audiences
• Ability to collaborate effectively with stakeholders across multiple departments
Preferred Qualifications
• Master's degree in Analytics, Data Science, or a related field
• Direct experience with Epicor ERP (Kinetic) and/or ADP reporting
• Experience in construction, manufacturing, or modular construction environments
• ETL or data-pipeline experience
• Familiarity with data governance frameworks such as DAMA-DMBOK
• Experience using Python, R, or similar analytical scripting tools
• Microsoft Power BI Data Analyst (PL-300), Certified Analytics Professional (CAP), or equivalent certification
What We Offer
• Competitive compensation based on experience
• Opportunity to work with enterprise-level ERP and HRIS platforms
• Exposure to finance, operations, project management, and workforce analytics
• Opportunity to contribute to high-impact reporting and decision-making initiatives
• Collaborative, data-driven work environment
• Valuable experience supporting ERP and HRIS reporting, analytics, and process improvement efforts
• Potential consideration for future opportunities based on business needs and performance
Culture & Growth
• Opportunity to help shape reporting standards, KPI definitions, and data governance practices
• Collaborative environment focused on continuous improvement and innovation
• Team-oriented, respectful workplace culture
• Faith-based company values and leadership
• Weekly paid Bible study during work hours
• Supportive environment focused on personal, professional, and spiritual growth
Our C.H.R.I.S.T. Values
• Creative - Finding clearer, simpler ways to represent complex data so the business can act on it
• Honorable - Acting with integrity, transparency, and ethical conduct in all reporting and analysis
• Respectful - Treating every stakeholder with dignity and communicating findings in language they can understand
• Innovative - Continuously improving models, reporting processes, definitions, and automation
• Synergistic - Building shared data assets and collaborating across departments to maximize organizational value
• Total Ownership - Taking accountability for data quality from source reconciliation through final reporting
CREATIVE MODULAR CONSTRUCTION LLC is an EEO Employer - M/F/Disability/Protected Veteran Status

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