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Data Analyst Data Science Jobs in Springfield, MO

Bachelor's degree in Data Science, Computer Science, or a related field * Minimum of 3-5 years of experience in data management, analytics, or similar, preferably within a marketing environment

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 ...

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 ...

... 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 ...

... 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 ...

Data Entry Specialist

Springfield, MO · On-site

$16 - $21.50/hr

... analyze, identify, query and resolve data issues and inconsistencies, ensuring quality reporting standards are met through an established Quality Control process. * Customer service, including ...

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Showing results 1-20

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 Jul 29, 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.

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 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.

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.
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:
Infographic showing various Data Analyst Data Science job openings in Springfield, MO as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 81% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $75,172 per year, or $36.1 per hour.

Enterprise Data Analyst

Husch Blackwell Llp

Springfield, MO • On-site, Remote

Full-time

Medical, Dental, Life, Retirement, PTO

Posted 5 days ago


Husch Blackwell rating

9.5

Company rating: 9.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

3rd of 34 rated law firms


Job description

Husch Blackwell LLP is a full-service litigation and business law firm with multiple locations across the United States, serving clients with domestic and international operations.

At Husch Blackwell we believe that diverse, equitable and inclusive teams lead to better outcomes. Husch Blackwell is committed to retaining, recruiting, developing, and promoting talented lawyers and business professionals with diverse backgrounds and experiences. We foster an engaged, diverse, and inclusive team culture of accountability and purpose that makes our Firm and our communities better.

Our firm is committed to attracting and retaining professionals who value each other and the service we provide by embracing Teamwork, Collaboration, Client Service, and Innovation. If you are a motivated professional looking for a long-term fit where you can grow in a role, and will be valued and empowered, then we invite you to apply to our Enterprise Data Analyst position. This position may be filled remotely or in a hybrid capacity in any of our Central and Eastern Time locations. Strong candidates located in Mountain Time will also be considered.

The Enterprise Data Analyst is a firmwide shared-services role within the Firm’s Data Science function. The analyst turns the Firm’s data, client data, and the extensive internal data the Firm maintains into clear, actionable insight, delivered primarily through Power BI dashboards and reports that teams across the Firm rely on. The role will initially support a key business unit, with scope expanding to serve additional practice groups and functions across the Firm over time. The right candidate will be skilled in the visual display of quantitative information and have a passion for high impact data storytelling. Essential functions include:

Data Analysis & Insight

  • Analyze large, complex datasets from client and internal Firm sources to identify trends, patterns, and actionable insights
  • Clean, transform, and structure data to ensure accuracy, consistency, and readiness for analysis
  • Apply statistical and data-modeling techniques to answer business questions and support decision-making
  • Leverage AI and generative-AI tools to accelerate analysis, automate routine tasks, and enhance data products
  • Translate stakeholder questions into clearly defined analytical problems, prioritizing work by impact and urgency

Dashboarding & Reporting

  • Design, build, and maintain Power BI dashboards that serve as the Firm’s primary, everyday reporting tools
  • Build automated, self-service reports and visualizations in Power BI and Tableau, tailored to different audiences across the Firm
  • Use data storytelling to deliver client-facing data presentations and executive-level reports that communicate findings clearly to key partners, clients, and other internal and external stakeholders, and drive action
  • Collaborate with the Data Science Information Design and Engineering function to deliver data visualization and information rich analyses across various media types
  • Streamline and standardize reporting processes to ensure timely, accurate delivery of key metrics

Data Management & Quality

  • Partner with the Data Engineering team to source, integrate, and validate data from across the Firm
  • Develop and apply data quality standards to ensure reliable, trustworthy outputs
  • Document data sources, definitions, and methodologies to support consistency and reuse
  • Maintain and enhance existing datasets, models, and reporting pipelines

Cross-Functional Collaboration

  • Partner with teams across the Firm; including Finance and client-facing groups to gather requirements and align on objectives
  • Work directly with internal stakeholders and, where appropriate, clients to understand needs and deliver solutions
  • Connect analytical findings to business outcomes and Firm priorities

Continuous Improvement & Growth

  • Share knowledge and best practices to elevate data and analytics capabilities across the Firm
  • Identify opportunities to automate, improve, and scale analytics as the function grows
  • Contribute to building out the Firm’s enterprise data and analytics capabilities over time
  • Develop and improve reporting and business intelligence techniques to align the firm with leading edge information and business intelligence delivery
  • Engage in research and study to continuously improve the Firm’s reporting and business intelligence

POSITION REQUIREMENTS

  • Bachelor’s degree in statistics, economics, computer science, information design, or a related quantitative communications field; commensurate professional and educational experience shall also qualify
  • 3+ years in data analysis, business intelligence, or a related analytical role (the role may be filled at more than one level; strong candidates earlier in their careers will also be considered)
  • Advanced, demonstrable proficiency in Power BI is required; including building, publishing, and maintaining production dashboards
  • Strong proficiency in Excel and SQL, with experience querying and working with large, complex datasets
  • Proficiency with basic statistical and analytical tools including the Python statistical ecosystem
  • Experience working with data warehouses, databases, and modern BI/data platforms
  • Strong data storytelling skills, with a proven ability to design clear, effective data visualizations and deliver client-facing presentations to partners, clients, and other internal and external stakeholders
  • Experience with statistical modeling, regression analysis, and null hypothesis significance testing
  • Proven ability to independently scope and lead complex data analysis projects
  • Experience analyzing financial and operational performance metrics and the drivers behind them
  • Fluent in translating complex data into clear implications and actionable recommendations for the business
  • Comfortable working with large, complex datasets and developing data quality standards
  • Experience working directly with senior stakeholders and, where appropriate, clients
  • Operates with a client-service mindset; responsive, proactive, and a trusted advisor
  • Comfortable working at both strategic and tactical levels
  • Thrives in fast-paced environments with shifting priorities
  • Strong attention to detail and ability to maintain accuracy under pressure
  • Eager to contribute beyond assigned tasks and play a key role in the growth of a new, firmwide analytics function
  • Understanding of data confidentiality and the sensitivity of legal and client information

Preferred Qualifications

  • Experience supporting multiple business units or functions in a shared-services or enterprise environment
  • Experience with data pipeline or ETL processes and working alongside data engineers
  • Experience applying AI and generative-AI tools to accelerate and enhance analytics
  • Familiarity and comfort with executive level communication and presentations

The above is intended to describe the general content of and requirements for the performance of this job. It is not to be construed as an exhaustive statement of essential functions, responsibilities, or requirements. The Firm will provide reasonable accommodations as necessary to allow an individual with a disability to apply for and/or perform the essential functions of a position. If you need assistance to accommodate a disability, please contact HR.

COMPENSATION AND BENEFITS

Employees are entitled to compensation commensurate with skill and experience. The exact compensation will vary based on skills, experience, location, and other factors permitted by law. The expected compensation ranges for this position in various states and jurisdictions are as follows:

  • State of California: $116,000 - $237,000
  • State of Colorado: $107,000 - $191,000
  • State of Illinois: $105,000 - $204,000
  • State of Maine: $79,000 - $182,000
  • State of Maryland: $113,000 - $171,000
  • State of Massachusetts: $116,000 - $222,000
  • State of Minnesota: $116,000 - $192,000
  • Jersey City, NJ: $126,000 - $229,000
  • State of New York: $108,000 - $234,000
  • State of Vermont: $115,000 - $220,000
  • State of Virginia: $76,000 - $220,000
  • State of Washington: $113,000 - $214,000
  • Washington, D.C.: $150,000 - $220,000

The above salaries do not include a discretionary bonus, however bonus opportunities are non-guaranteed, and are dependent upon individual and firm performance. Full-time employees receive benefits including: medical and dental coverage; life insurance; short-term and long-term disability insurance; pre-tax flexible spending account for certain medical and dependent care expenses; an employee assistance program; Paid Time Off; paid holidays; participation in a retirement plan program after meeting eligibility requirements; and more.

Please include a cover letter and resume when applying.

EOE/Minority/Female/Disabled/Vet. Principal Applicants Only.

#LI-Remote
#LI-KW1


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