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Scientist Python Jobs in Lancaster, PA (NOW HIRING)

Develop analytics solutions using Python and PySpark * Support data pipeline design, validation ... Collaborate with data science, engineering, and reporting teams to deliver standardized data ...

Develop analytics solutions using Python and PySpark * Support data pipeline design, validation ... Collaborate with data science, engineering, and reporting teams to deliver standardized data ...

Develop analytics solutions using Python and PySpark * Support data pipeline design, validation ... Collaborate with data science, engineering, and reporting teams to deliver standardized data ...

Operations AI Intern

Morgantown, PA · On-site

$14.75 - $19.50/hr

... Science, Data Science, Engineering, AI/ML, Industrial Engineering, or related field. * Foundational knowledge of machine learning concepts and data analysis. * Experience with Python, SQL, AI ...

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Scientist Python information

See Lancaster, PA salary details

$36.4K

$119.3K

$191K

How much do scientist python jobs pay per year?

As of Jul 21, 2026, the average yearly pay for scientist python in Lancaster, PA is $119,282.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,700.00 and $132,200.00 per year, depending on experience, location, and employer.

How do Scientist Python roles typically collaborate with other team members during research and development projects?

Scientist Python professionals frequently work in multidisciplinary teams, collaborating closely with data scientists, domain experts, and software engineers. They are often responsible for developing and implementing Python-based models or algorithms, then integrating their work with broader research goals or product pipelines. Regular communication, code reviews, and shared documentation are common practices to ensure alignment and reproducibility. This collaborative environment offers opportunities to learn from peers and contribute to diverse projects, fostering both technical and professional growth.

What does a Scientist Python do?

A Scientist Python, often referred to as a Python Scientist or Data Scientist specializing in Python, uses the Python programming language to analyze data, build predictive models, and solve scientific or business problems. They work with large datasets, apply statistical and machine learning techniques, and create visualizations to interpret results. Their work often involves writing code to clean, manipulate, and analyze data efficiently. Python's extensive libraries, such as Pandas, NumPy, and SciPy, make it a popular choice for scientific computing and data science tasks.

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

To thrive as a Scientist Python, you need strong programming skills in Python, a solid background in scientific methods or data analysis, and typically an advanced degree in a relevant field such as computer science, physics, or biology. Experience with data analysis libraries (e.g., NumPy, pandas, SciPy), machine learning frameworks (e.g., scikit-learn, TensorFlow), and version control systems is commonly required. Critical thinking, effective communication, and problem-solving abilities help distinguish top performers in this role. These skills enable efficient data-driven research, reproducible scientific workflows, and successful collaboration in multidisciplinary environments.

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

AspectScientist PythonData Analyst Python
Required CredentialsBachelor's or Master's in Science, Data Science, or related fields; Python proficiencyBachelor's in Statistics, Data Analysis, or related fields; Python skills
Work EnvironmentResearch labs, R&D departments, tech companiesBusiness intelligence teams, marketing, finance departments
Employer & Industry UsageResearch institutions, tech firms, healthcareCorporate, finance, retail, marketing
Common Search & ComparisonYesYes

Scientist Python and Data Analyst Python roles share similar skills like Python programming and data handling. However, Scientists typically focus on research, experimentation, and developing new models, often working in research-heavy environments. Data Analysts concentrate on interpreting existing data to inform business decisions, working mainly in corporate settings. Both roles require strong analytical skills and Python expertise, but their focus and work environments differ significantly.

What are popular job titles related to Scientist Python jobs in Lancaster, PA? For Scientist Python jobs in Lancaster, PA, the most frequently searched job titles are:
What job categories do people searching Scientist Python jobs in Lancaster, PA look for? The top searched job categories for Scientist Python jobs in Lancaster, PA are:
What cities near Lancaster, PA are hiring for Scientist Python jobs? Cities near Lancaster, PA with the most Scientist Python job openings:

Mathematical Statistician (Data Scientist) - Direct Hire

Criminal Investigation & Law Enforcement | IRS Careers

Lancaster, PA • On-site

$74K/yr

Other

Posted 12 days ago


Job description

WHAT IS DATA AND ANALYTICS?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO- Data and Analytics Office (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
IOR BASIC REQUIREMENTS GS-1529 Mathematical Statistician (Data Scientist):
You must have a degree that included courses in mathematics and statistics totaling at least 24 semester hours. This course work must have included a minimum of 12 semester hours of mathematics, and 6 semester hours were in statistics. Courses acceptable toward meeting the mathematics course requirement must have included at least four of the following: differential calculus, integral calculus, advanced calculus, theory of equations, vector analysis, advanced algebra, linear algebra, mathematical logic, differential equations, or any other advanced course in mathematics for which one of these was a prerequisite. Courses in mathematical statistics or probability theory with a prerequisite of elementary calculus or more advanced courses will be accepted toward meeting the mathematics requirements, with the provision that the same course cannot be counted toward both the mathematics and the statistics requirement.
OR
Combination of education and experience -- includes at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as described above; and Experience that showed evidence of statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying known statistical techniques to data such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
GS-1529-11 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science projects.
  2. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  3. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  4. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  5. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  6. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
OR
EDUCATION: You may substitute education for specialized experience specialized experience as follows: Three (3) full academic years of progressively higher-level graduate education in Mathematics, statistics, or related fields.
OR
Ph. D. or equivalent doctoral degree Mathematics, statistics, or related field of study from an accredited college or university.
OR
Combination of education and experience: A combination of qualifying graduate education and experience equivalent to the amount required.
GS-1529-12 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience applying knowledge of statistical theories, principles, concepts and practices that relate to experimental design, data analysis, sampling, forecasting, quality control, and operations research to understand, model and improve program operations.
  2. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  3. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  4. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  5. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  6. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  7. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.

GS-1529-13 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service.
Examples of specialized experience for this position may include:
  1. Experience applying project management principles on a data science project.
  2. Experience planning and executing a variety of data science and/or analytics projects.
  3. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  4. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  5. Experience working with multiple data types and formats as a part of a data science project.
  6. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  7. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  8. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  9. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER