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Data Science Jobs in Springfield, MA (NOW HIRING)

Tiger Analytics Inc.

GenAI Data Engineer

Hartford, CT · On-site +1

$115K - $138K/yr

Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from ...

Tiger Analytics Inc.

GenAI Data Engineer

Hartford, CT · On-site

$115K - $138K/yr

Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from ...

MANTECH

Senior Data Scientist

Springfield, MA · On-site

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 ...

Amicis Global

Data Engineer

Hartford, CT · On-site

$70 - $80/hr

Bachelor's degree in Computer Science, Data Science, Information Technology, or related field. Hands-on experience with Snowflake (including SnowSQL, Snowpipe). Expert-level skills in AWS services ...

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All JobsData Science JobsData Science Jobs in Springfield, MA

Data Science information

See Springfield, MA salary details

$37.4K

$122.3K

$195.8K

How much do data science jobs pay per year?

As of Sep 13, 2026, the average yearly pay for data science 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 is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

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, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

Is a data scientist in high demand?

Data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.
More about Data Science jobs

What are the most commonly searched types of Data Science jobs in Springfield, MA?

The most popular types of Data Science jobs in Springfield, MA are:

What are popular job titles related to Data Science jobs in Springfield, MA?

For Data Science jobs in Springfield, MA, the most frequently searched job titles are:

What job categories do people searching Data Science jobs in Springfield, MA look for?

The top searched job categories for Data Science jobs in Springfield, MA are:

What cities near Springfield, MA are hiring for Data Science jobs?

Cities near Springfield, MA with the most Data Science job openings:

Data Science jobs near you
Infographic showing various Data Science job openings in Springfield, MA as of September 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 100% In-person job distribution, with an average salary of $122,309 per year, or $58.8 per hour.

GenAI Data Engineer

Hartford, CT • On-site, Remote

Tiger Analytics Inc.
Business Management Consulting • 201 - 500 employees
Learn more about Tiger Analytics Inc.external

$115K - $138K/yr

Full-time

Re-posted 16 days ago

Job description

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world.
We are seeking an experienced Data Engineer with expertise in Dataiku to join our data team. As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines, data integration processes, and data infrastructure. You will collaborate closely with data scientists, analysts, and other stakeholders to ensure efficient data flow and support data-driven decision making across the organization.
Requirements
  • Design and implement robust data pipelines that ingest, process, and store unstructured data formats at scale within Snowflake and GCP.
  • Leverage Snowflake's unstructured data capabilities (Directory Tables, Scoped URLs, Snowpark) to make "dark data" queryable and actionable.
  • Build and maintain cloud-native ETL/ELT processes using BigQuery, Cloud Storage, and Dataflow, ensuring seamless integration between GCP and Snowflake.
  • Instead of just using LLMs, you will integrate AI tools (OCR, NLP entities, Document AI) into the engineering flow to transform unstructured blobs into structured insights.
  • Tune complex SQL queries and Python-based processing jobs to handle petabyte-scale environments efficiently.

Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, challenging, and entrepreneurial environment, with a high degree of individual responsibility.

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