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Data Scientist Jobs in Springfield, MA (NOW HIRING)

Deloitte

AI Solutions Architect

Hartford, CT · On-site

$63.50 - $83.75/hr

Collaborating with architects, engineers, data scientists, and business stakeholders to align technical solutions with business requirements and implementation priorities * Overseeing execution of AI ...

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All JobsData Scientist JobsData Scientist Jobs in Springfield, MA

Data Scientist information

See Springfield, MA salary details

$37.4K

$122.3K

$195.8K

How much do data scientist jobs pay per year?

As of Jul 19, 2026, the average yearly pay for data scientist in Springfield, MA is $122,309.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,200.00 and $135,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks, data visualization tools, and big data platforms like TensorFlow, Tableau, and Hadoop, as well as certifications in data science, are highly valued. Excellent problem-solving skills, curiosity, and the ability to communicate complex findings clearly set outstanding data scientists apart. These skills and qualities are crucial for extracting actionable insights from data, driving business decisions, and collaborating effectively with stakeholders.

What Do Data Scientists Do?

Data scientists collect, confirm, and interpret data to determine useful information for their employer. They help organizations identify patterns and trends in their data to provide information about lucrative opportunities, necessary improvements, and potential innovations. The information data scientists get from the records they gather helps businesses make major decisions in critical areas, such as product development, sales and marketing techniques, and client retention. Data scientists are highly educated; the majority of them have at least a master's degrees, and many have doctorates. Data scientists are valuable members of organizations in many different industries, including pharmaceuticals, manufacturing, and banking.

What careers can I do with data science?

Data scientists can pursue careers in fields such as machine learning engineering, data analysis, business intelligence, data engineering, and research roles. These positions often require skills in programming, statistical analysis, and tools like Python, R, or SQL, and may involve working in industries like finance, healthcare, technology, or marketing.

Is a data scientist job still in-demand?

Yes, data scientist roles remain in high demand across various industries due to the increasing reliance on data-driven decision making. Skills in machine learning, statistical analysis, and programming languages like Python or R are highly valued, and the field continues to grow as organizations seek to leverage big data for competitive advantage.

What are Data Scientists?

Data Scientists are professionals who use statistical, analytical, and programming skills to collect, analyze, and interpret large volumes of data. They extract insights and trends from complex data sets to help organizations make data-driven decisions. Data Scientists often work with machine learning, data mining, and big data technologies to build predictive models and solve business problems. Their work bridges the gap between technical data analysis and actionable business strategy.

What does a data scientist do exactly?

A data scientist analyzes large datasets to extract insights, build predictive models, and support decision-making. They use statistical techniques, programming languages like Python or R, and tools such as SQL and machine learning algorithms to interpret data and solve complex problems.

Is 30 too late for data science?

Data scientists can enter the field at any age, including 30 or older, as success depends on skills, experience, and continuous learning. Many professionals transition into data science from different backgrounds by acquiring relevant skills such as programming, statistics, and machine learning through courses or certifications. Age is not a barrier if you develop a strong portfolio and stay current with industry tools and techniques.

What is the difference between Data Scientist vs Data Analyst?

AspectData Scientist
Required CredentialsDegree in Computer Science, Statistics, or related field; often requires advanced degrees
Work EnvironmentResearch and development, predictive modeling, machine learning projects
Employer & Industry UsageTech companies, finance, healthcare, consulting firms
Common Search & ComparisonOften compared due to overlapping skills in data analysis and modeling

Data Scientists focus on building predictive models, advanced analytics, and machine learning, often requiring higher-level technical skills and education. Data Analysts primarily interpret existing data, generate reports, and support decision-making with descriptive analytics. While both roles analyze data, Data Scientists handle complex modeling and predictive tasks, whereas Data Analysts focus on data interpretation and reporting.

What are some typical projects Data Scientists work on, and how do they collaborate with other teams?

Data Scientists often work on projects such as building predictive models, analyzing large datasets to uncover trends, and developing data-driven solutions to business problems. They regularly collaborate with cross-functional teams, including software engineers, data engineers, and business analysts, to ensure that their insights are actionable and aligned with business goals. Effective communication and teamwork are essential, as Data Scientists frequently need to present complex findings to non-technical stakeholders and incorporate feedback from various departments.
More about Data Scientist jobs
What are the most commonly searched types of Data Scientist jobs in Springfield, MA? The most popular types of Data Scientist jobs in Springfield, MA are:
What are popular job titles related to Data Scientist jobs in Springfield, MA? For Data Scientist jobs in Springfield, MA, the most frequently searched job titles are:
What job categories do people searching Data Scientist jobs in Springfield, MA look for? The top searched job categories for Data Scientist jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Data Scientist jobs? Cities near Springfield, MA with the most Data Scientist job openings:
Data Scientist jobs near you

Research Fellow - Artificial Intelligence/Machine Learning

UMass Amherst

Amherst, MA • On-site

$70K - $110K/yr

Other

Posted 12 days ago

Job description

Title: Research Fellow - AI/ML

Executive Area: Academic Affairs

College/School/MBU: College of Information & Computer Sciences

Department: Computer Science

Work Location: Amherst

Schedule:Full Time

Work Arrangement:Onsite

Job Summary

The Center for Data Science and Artificial Intelligence (CDSAI) in the Manning College of Information and Computer Sciences (CICS) is seeking a Research Fellow to join our applied AI and machine learning team. In this role, you will design, develop, and deploy machine learning and AI solutions that support research initiatives across the university and partner institutions. You will work on technical projects from concept to production, implement best practices, and bridge cutting-edge AI research with practical, scalable applications. You will work closely with researchers, faculty, and external stakeholders to transform complex requirements into robust, deployed ML systems.

Essential Functions

Design, develop, and deploy machine learning and deep learning models for applied research projects.
Manage multiple concurrent projects, ensuring timely delivery and alignment with stakeholder needs.
Build and maintain MLOps pipelines for model training, evaluation, versioning, and deployment.
Implement scalable ML infrastructure across cloud platforms (e.g., AWS, GCP, Azure) and on-premises environments.
Develop APIs and integration layers to embed ML capabilities into applications and research workflows.
Collaborate with researchers and non-technical stakeholders to translate research questions into technical solutions.
Document technical implementations, model architectures, and research methodologies to ensure reproducibility.
Stay current with emerging AI/ML techniques and evaluate their applicability to Center projects.

Other Functions

Other duties as assigned.

Minimum Qualifications

Bachelor's degree or higher in Computer Science, Data Science, Machine Learning, or a related field.
Strong programming expertise in Python, with experience in ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
Demonstrated experience deploying ML models to production environments.
Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, DVC, Docker, CI/CD for ML).
Experience with cloud-based ML services and infrastructure (e.g., AWS SageMaker, GCP Vertex AI, Azure ML).
Ability to manage multiple projects and guide junior engineers or collaborators.
Excellent written and verbal communication skills for working with technical and non-technical stakeholders.
Demonstrated ability to work independently and solve complex technical challenges.

Preferred Qualifications

Experience with LLMs, generative AI, and prompt engineering.
Familiarity with NLP, computer vision, or time-series modeling.
Experience with distributed computing frameworks (e.g., Spark, Ray, Dask).
Background in data engineering and pipeline orchestration (e.g., Airflow, Prefect).
Prior experience in academic or research-focused settings.
Experience mentoring or leading technical teams.
Familiarity with responsible AI practices and model interpretability.

Working Conditions

Work is performed in a standard office or indoor university environment and involves minimal physical exertion.

Work Schedule and Work Arrangement

Typical office hours between 8:00 AM and 5:00 PM.

Salary Information

The salary range is $70,000-$110,000, commensurate with experience and qualifications.

Special Instructions for Applicants

Alongside your application, please include CV or resume detailing your academic and professional background, a cover letter describing your relevant experience and research interests, and the contact information for three (3) professional references.

This position will remain open for the time period required by any applicable collective bargaining agreement and will continue until a suitable candidate pool is identified. Interested applicants are strongly encouraged to apply early.

Apply