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Senior Data Scientist information

See Springfield, IL salary details

$41.1K

$141.2K

$199.2K

How much do senior data scientist jobs pay per year?

As of Sep 9, 2026, the average yearly pay for senior data scientist in Springfield, IL is $141,193.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,400.00 and $165,000.00 per year, depending on experience, location, and employer.

What is a senior data scientist?

A senior data scientist does complex data analysis. Job duties include gathering data and writing reports that can help people make decisions. In some cases, they may offer machine learning which is a way to help computers process and understand data. A senior data scientist may also be asked to formulate an algorithm to solve work problems. You need statistics and programming knowledge to be successful in this career.

What does a senior data scientist do?

A Senior Data Scientist leads advanced analytical projects, utilizing statistical modeling, machine learning, and data mining techniques to extract insights from large datasets. They collaborate with cross-functional teams to identify business opportunities, design predictive models, and communicate findings to stakeholders. In addition to technical expertise, they often mentor junior data scientists, help define data strategies, and ensure best practices in data analysis and model deployment.

What are the key skills and qualifications needed to thrive as a senior data scientist, and why are they important?

To thrive as a Senior Data Scientist, you need advanced expertise in statistics, machine learning, data analysis, and programming, typically supported by a degree in a quantitative field and several years of experience. Familiarity with tools like Python, R, SQL, cloud platforms, and machine learning frameworks, as well as relevant certifications such as AWS Certified Machine Learning or TensorFlow Developer, is highly valuable. Strong problem-solving abilities, communication skills, and leadership qualities help in translating data insights into actionable business strategies and mentoring junior team members. These skills and qualities are crucial for driving impactful data-driven decisions and fostering innovation within organizations.

What are some of the main challenges senior data scientists face when leading cross-functional projects?

Senior Data Scientists often encounter challenges such as aligning project goals across diverse teams, managing expectations of non-technical stakeholders, and ensuring data quality and accessibility. Balancing long-term research initiatives with immediate business needs can also be demanding. Effective communication, project management skills, and the ability to translate complex findings into actionable insights are essential for overcoming these hurdles and driving successful outcomes.

What is the difference between Senior Data Scientist vs Data Analyst?

AspectSenior Data ScientistData Analyst
Required CredentialsMaster's or PhD in Data Science, Statistics, or related fieldBachelor's degree in related field, often with certifications
Work EnvironmentAdvanced analytics, modeling, and machine learning projectsData reporting, visualization, and basic analysis
Employer & Industry UsageTech, finance, healthcare, and large enterprisesRetail, marketing, small to medium businesses

While both roles involve working with data, Senior Data Scientists focus on complex modeling and predictive analytics, whereas Data Analysts primarily handle data reporting and visualization. The Senior Data Scientist role requires advanced technical skills and higher education, making it suitable for more complex projects in larger organizations.

What is a senior data scientist's salary?

A senior data scientist's salary typically ranges from $100,000 to $150,000 annually, depending on experience, location, and industry. They often have advanced skills in machine learning, statistical analysis, and proficiency with tools like Python or R.
More about Senior Data Scientist jobs

What are the most commonly searched types of Data Scientist jobs in Springfield, IL?

The most popular types of Data Scientist jobs in Springfield, IL are:

What are popular job titles related to Senior Data Scientist jobs in Springfield, IL?

For Senior Data Scientist jobs in Springfield, IL, the most frequently searched job titles are:

What cities near Springfield, IL are hiring for Senior Data Scientist jobs?

Cities near Springfield, IL with the most Senior Data Scientist job openings:

Senior Data Scientist jobs near you
Infographic showing various Senior Data Scientist job openings in Springfield, IL as of August 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 77% In-person, and 23% Remote job distribution, with an average salary of $141,193 per year, or $67.9 per hour.

Senior Data Engineer (ETL / Python Developer)

Springfield, IL • On-site

CSpring
51 - 200 employees
Learn more about CSpringexternal

Full-time

Posted 26 days ago

Job description

Description

At CSpring, we believe in the power of data to drive decisions and real-world impact. We're a purpose-driven consulting firm specializing in data strategy, data engineering, and data analytics. Our clients span the public and private sectors, and our work helps them solve complex problems, gain insights, and achieve measurable results.  


We're seeking talented professionals who are collaborative, curious, and committed to making a difference that thrive at the intersection of data, technology, and business strategy. Whether you're passionate about transforming public programs, enabling executive decision-making, or modernizing legacy systems, you'll find meaningful work and purpose here.


Why You'll Love Working Here

  • Purposeful Projects - Improve systems that serve real people by delivering smarter data, streamlined processes, and strategic insight.
  • People-First Culture - We're as committed to your growth as we are to delivering high-impact solutions. You'll find support, autonomy, and community here.
  • Strategic, Hands-On Work - From data architecture and documentation to client workshops and solution delivery, you'll influence every step of the process.
  • Collaborative Trust - Our clients rely on us to listen carefully, deliver consistently, and guide wisely. We partner with integrity, curiosity, and heart.

What You'll Do

  • Design, develop, and maintain enterprise ETL pipelines using Azure Data Factory (ADF), Informatica PowerCenter, and Python-based frameworks.
  • Build and optimize scalable data processing solutions using Python, Spark, and Databricks.
  • Write and optimize SQL and stored procedures across relational platforms such as Snowflake, Oracle, and SQL Server.
  • Follow data engineering best practices for performance, reliability, reusability, and security.
  • Support Medicaid analytics and federal reporting initiatives (e.g., T-MSIS, PERM, MARS, Quality of Care).
  • Develop robust data validation, reconciliation, and audit-traceable data pipelines.
  • Collaborate with analysts, QA, and reporting teams to ensure data quality, accuracy, and timeliness.
  • Participate in cloud migration and modernization initiatives within Azure-based architectures.
  • Support production operations, incident resolution, and root cause analysis. 
  • Participate in code reviews, source control, and CI/CD processes using Azure DevOps and GitHub.

Requirements

  • 5+ years of data engineering experience with a focus on enterprise data warehousing.
  • 5+ years of hands-on ETL development using Informatica PowerCenter, Teradata, Azure Data Factory, or similar tools.
  • 5+ years of Python development for data engineering and automation.
  • 5+ years of Teradata experience, including Teradata loader utilities.
  • 3+ years of experience with Spark-based processing frameworks (Databricks or equivalent).
  • Solid SQL expertise and experience with relational databases (such as Snowflake, Oracle, SQL Server).
  • 3+ years of experience with Snowflake using SnowSQL and Snowpark (Python).
  • Experience with source control and DevOps practices (Azure DevOps, GitHub, CI/CD).
  • Proven solid analytical, problem-solving, and troubleshooting skills.
  • Periodic travel may be required based on project or customer needs.

Preferred Qualifications

  • Bachelor's degree or higher in Computer Science, Engineering, Analytics, or a related field.
  • Azure certifications related to data engineering or analytics.
  • Experience supporting State Medicaid EDW or MMIS analytics environments.
  • Healthcare or public sector analytics experience (Medicaid / Medicare preferred).
  • Data modeling experience in enterprise data warehouse environments.
  • Scripting experience (PowerShell, Bash) for automation and orchestration.
  • Experience designing or consuming APIs (REST) within data platforms.
  • Familiarity with data quality frameworks, reconciliation, and audit support.

Come Build With Us

At CSpring, we unlock the potential of people and data. If you're ready to lead meaningful projects, collaborate with passionate teams, and grow your career in a people-first consulting environment-apply today!

Apply