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Data Scientist Jobs in Springfield, MA (NOW HIRING)

Role: Data Scientist Location/s: Hartford, CT (or) Stamford, CT (or) Morristown, NJ [Hybrid] (or) Remote for other USA locations Job Type: Contract * Data scientists develop robust, efficient, and ...

... Ability Data Science • Experience with machine learning, AI, and cognitive service engine models • Experience with programming languages like SQL, Python, R, and Scala • Using analytics ...

The Senior Data Scientist leads the integration and application of advanced data analytics to solve complex business challenges and enhance mission security. The contractor will serve as a subject ...

Data Scientist

Windsor, CT · On-site

$117K - $146K/yr

Work independently and collaboratively on analytical, programming, modelling, and data management activities * Map out and document problem statements, project requirements and associated workflows ...

As a Lead Data Scientist for NA PC Analytics, you will perform quantitative data analysis to enable organizational decision making and develop solutions to complex business problems and create value ...

MANTECH seeks a motivated, career and customer-oriented Senior Data Scientist to join our team in Springfield, VA . This is a full-time onsite position. Responsibilities include but are not limited ...

Lead Data Scientist

Manchester, CT · On-site

$144K - $198K/yr

The lead data scientist will build data, analytics, and AI solutions to support SIOP (Sales, Inventory, Operations Planning) transformation and delivery business impact on inventory and customer ...

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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 18, 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.
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

Saransh Inc

Hartford, CT • On-site

Contractor

Re-posted 6 days ago


Job description

Role: Data Scientist
Location/s: Hartford, CT (or) Stamford, CT (or) Morristown, NJ [Hybrid] (or) Remote for other USA locations
Job Type: Contract
 
Job Description:
  • Data scientists develop robust, efficient, and scalable AI models to extract valuable information from various unstructured data sources, including but not limited to PDFs, Word documents, and Excel files.
  • They design and implement logic to process this data and generate meaningful outputs to support user decision-making.
  • Candidates must possess extensive experience with Python, large language models (LLMs), machine learning techniques, data structures, and algorithms.
  • Their expertise enables them to create innovative solutions that handle complex data processing challenges effectively.