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Data Science Jobs in Indiana, PA (NOW HIRING)

S and T Bank

Data & Analytics Senior Analyst

Indiana, PA · On-site

$48K - $115K/yr

Requires a four-year degree in data science, computer science, applied mathematics, statistics, business, economics, and/or quantitative discipline preferred. Experience: Two to five years general ...

First Quality Retail Services

Data Engineer

Home, PA · On-site +1

$102K - $122K/yr

Collaborate with business stakeholders, data engineers, and data scientists to understand data requirements and design scalable and flexible data models. * Develop data ingestion pipelines and ...

Deckers

Sr. Manager, Data & ML Engineering

Indiana, PA · Remote

Bachelor's degree required, preferably in Computer Science, Engineering, or related technical field; Master's degree preferred * AWS certifications (Data, Machine Learning, or Solution Architecture ...

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All JobsData Science JobsData Science Jobs in Indiana, PA

Data Science information

See Indiana, PA salary details

$34.3K

$112.2K

$179.6K

How much do data science jobs pay per year?

As of Jul 13, 2026, the average yearly pay for data science in Indiana, PA is $112,176.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $124,300.00 per year, depending on experience, location, and employer.

Is data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

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.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

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 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 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.

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.

What work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

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.
More about Data Science jobs
What are the most commonly searched types of Data Science jobs in Indiana, PA? The most popular types of Data Science jobs in Indiana, PA are:
What job categories do people searching Data Science jobs in Indiana, PA look for? The top searched job categories for Data Science jobs in Indiana, PA are:
What cities near Indiana, PA are hiring for Data Science jobs? Cities near Indiana, PA with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Indiana, PA as of July 2026, with employment types broken down into 100% Full Time. Highlights an 62% In-person, and 38% Remote job distribution, with an average salary of $112,176 per year, or $53.9 per hour.
SR. DATA SCIENCE ENGINEER SPEC-DATA SCIENTIST

SR. DATA SCIENCE ENGINEER SPEC-DATA SCIENTIST

Concurrent Technologies Corporation

Johnstown, PA • On-site, Remote

Full-time

Posted 5 days ago

Job description

SR DATA SCIENCE ENGINEER SPEC-DATA SCIENTIST
Concurrent Technologies Corporation
Johnstown, PA or Telecommute
Minimum Clearance Required: N/A
Clearance Level Must Be Able to Obtain: N/A
Employee Background Check Required
Concurrent Technologies Corporation (CTC) an independent, nonprofit applied scientific research and development organization. Is seeking a Sr. Data Science Engineer Spec-Data Scientist, you'll be part of the internal Information Technology team that keeps CTC's business operations running efficiently. Supporting employees across the organization, you'll contribute to a collaborative, customer-focused environment where technology enables engineers, researchers, and business professionals to accomplish their mission. CTC values teamwork, innovation, continuous learning, and exceptional customer service, providing opportunities to expand your technical skills while building a rewarding career with an organization dedicated to making a meaningful impact.
Key Responsibilities:
  • Collaborate with business leaders to identify high-impact business problems and translate them into data science and data analysis projects.
  • Collect, process, and analyze complex datasets from various sources to identify trends, patterns, and insights that inform business strategy.
  • Develop and implement predictive models and machine learning algorithms to solve business problems, such as forecasting, customer segmentation, and optimization.
  • Develop and maintain detailed, compelling dashboards and reports for both technical and non-technical audiences using business intelligence (BI) tools.
  • Perform exploratory data analysis (EDA) and statistical analysis to uncover patterns, trends, and anomalies.
  • Create clear, compelling, and actionable data visualizations and reports to communicate complex findings to both technical and non-technical audiences.
  • Design and execute A/B tests and other experiments to measure the impact of different initiatives.
  • Work with data engineers to build and improve data pipelines, ensuring data quality and accessibility.

Basic Qualifications:
  • Bachelor's or Master's degree in a quantitative field such as Statistics, Mathematics, Computer Science, or Economics.
  • 3-5 years of hands-on experience in a Data Scientist or Senior Data Analyst role.
  • Programming: Strong proficiency in Python (including libraries like Pandas, NumPy, and Scikit-learn), SQL, and PySpark.
  • Statistics and ML: Solid understanding of statistical analysis, data mining techniques, and machine learning algorithms (e.g., classification, regression, clustering, and decision trees).
  • Communication: Excellent verbal and written communication skills with the ability to tell a story with data.
  • Problem-Solving: Proven ability to approach complex problems with a structured, analytical, and inquisitive mindset.

Preferred Qualifications:
  • Experience with cloud-based data platforms (e.g., AWS, Azure, GCP).
  • Experience with big data technologies (e.g., Spark, Hadoop).
  • Experience with data visualization and analysis tools (e.g., Tableau, Power BI, Matplotlib, R, SAS).
  • Experience with natural language processing (NLP) or other forms of text analysis.
  • Knowledge of experimental design and causal inference techniques.
  • Experience in research & development, government contracting, and/or highly regulated industry domains.

Why CTC?
  • Our teams at CTC are passionate and thrive on collaboration in a team environment.
  • When we encounter a difficult problem, we have a variety of talented and diverse employees that work together to solve the toughest challenges.
  • Competitive salary and benefits package.
  • Although our work at CTC is extremely important, we also recognize the need for our employees to maintain a proper mix of work and personal life.
  • Visit www.ctc.com to learn more!

Join us! CTC offers exceptional career growth, cutting edge technology, educational opportunities, and recognition for quality work.
https://concurrent-technologies-corporation.breezy.hr/
Staffing Requisition: SR#2026-0087
"We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability status, protected veteran status, or any other characteristic protected by law."

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