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Data Science Degree Jobs in Rochester, NY (NOW HIRING)

Data Solutions Engineer

Rochester, NY · On-site

$98K - $160K/yr

Bachelor's Degree in Computer Science, Data Science, Engineering, or related field - Required * 7 years of experience in data engineering, software engineering, systems integration, or a related ...

Data Solutions Engineer

Rochester, NY · On-site +1

$91K - $156K/yr

Bachelor's Degree in Computer Science, Data Science, Engineering, or related field - Required * 7 years of experience in data engineering, software engineering, systems integration, or a related ...

Data Architect - Remote

Rochester, NY · Remote

$120K - $173K/yr

Experience with slowly-changing dimensions (SCDs) and entity resolution across systems * BS degree in Computer Science, Data Science, Engineering, or equivalent experience Why Join Mindex? For more ...

Data Architect - Remote

Rochester, NY · Remote

$120K - $173K/yr

Experience with slowly-changing dimensions (SCDs) and entity resolution across systems * BS degree in Computer Science, Data Science, Engineering, or equivalent experience Why Join Mindex? For more ...

Data Engineer - Remote

Rochester, NY · On-site +1

$90K - $140K/yr

Proficiency in Python for data processing and pipeline support * BS degree in Computer Science, Data Science, Engineering, or equivalent experience Why Join Mindex? For more than 30 years, Mindex has ...

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Data Science Degree information

See Rochester, NY salary details

$37K

$121.2K

$194K

How much do data science degree jobs pay per year?

As of Jul 18, 2026, the average yearly pay for data science degree in Rochester, NY is $121,157.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,200.00 and $134,200.00 per year, depending on experience, location, and employer.

What is the difference between Data Science Degree vs Data Analyst?

AspectData Science DegreeData Analyst
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fieldsBachelor's in Statistics, Mathematics, or related fields
Work EnvironmentResearch, modeling, developing algorithms, often in tech or finance industriesData cleaning, reporting, visualization, supporting business decisions
Employer & Industry UsageTech companies, finance, healthcare, academiaRetail, marketing, finance, healthcare

Data Science Degree programs focus on advanced analytics, machine learning, and programming, preparing individuals for complex modeling roles. Data Analysts typically handle data processing, visualization, and reporting to support decision-making. While both roles require strong analytical skills, Data Science degrees emphasize technical and statistical expertise, whereas Data Analysts focus on interpreting data for business insights.

What is a Data Science degree?

A Data Science degree is an academic program that prepares students to analyze, interpret, and derive insights from complex data sets using statistical, computational, and machine learning techniques. The curriculum typically includes coursework in mathematics, statistics, computer science, and specialized data science methods. Graduates are equipped with the skills to work in a variety of industries, tackling real-world problems by leveraging data-driven decision making. This degree can be pursued at the undergraduate or graduate level, and often includes hands-on projects and internships.

What types of real-world projects or team collaborations can I expect to work on after earning a Data Science degree?

After earning a Data Science degree, you can expect to engage in a variety of real-world projects such as building predictive models, analyzing large datasets to uncover business insights, and developing data-driven solutions for organizational challenges. Data scientists often collaborate closely with cross-functional teams, including software engineers, business analysts, and domain experts, to translate complex data findings into actionable strategies. These collaborations not only enhance your technical skills but also provide valuable experience in communication and project management, which are essential for career growth in this field.

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 mathematics, statistics, and programming, typically supported by a degree in data science, computer science, or a related field. Proficiency in technical tools such as Python or R, SQL, and machine learning frameworks, along with relevant certifications, is highly valued. Strong problem-solving abilities, effective communication, and curiosity help set apart top-performing data scientists. These skills are crucial for extracting actionable insights from data, collaborating with stakeholders, and driving data-driven decision-making.
What are popular job titles related to Data Science Degree jobs in Rochester, NY? For Data Science Degree jobs in Rochester, NY, the most frequently searched job titles are:
What job categories do people searching Data Science Degree jobs in Rochester, NY look for? The top searched job categories for Data Science Degree jobs in Rochester, NY are:
What cities near Rochester, NY are hiring for Data Science Degree jobs? Cities near Rochester, NY with the most Data Science Degree job openings:
Data Scientist-Direct Hire

Data Scientist-Direct Hire

US Department of the Treasury

Rochester, NY • On-site

$74K/yr

Other

Posted 13 days ago


U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

238th of 693 rated public administrative organizations


Job description

WHAT IS DATA AND ANALYTICS (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)?
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
  • 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.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS All GRADES: EDUCATION:
You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education with at least 30 semester hours related to Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
EDUCATION/SPECIALIZED EXPERIENCE FOR GS-11: In addition to meeting basic requirements, to be eligible for this position, you must have at least one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal Service. Specialized experience for this position includes: Applying descriptive or inferential statistical methods to analyze data, identify trends or patterns, evaluate results, and develop findings, reports, or recommendations; Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, analyze, or prepare data for analysis; Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform); Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings; and Creating reports, dashboards, visualizations, written summaries, or presentations to communicate statistical or technical findings to technical or non-technical audiences.
OR
EDUCATION: You may substitute education for specialized experience as follows: A Ph.D. or equivalent doctoral degree as described in the basic requirements in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
Three (3) full academic years of progressively higher-level graduate education leading to a PH.D or equivalent doctoral degree in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education.
SPECIALIZED EXPERIENCE GRADE 12: In addition to the basic requirements above, to be eligible for this position at the GS-12 level, 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. Specialized experience for this position includes experience performing all the following:
  • Planning and carrying out data analysis assignments by applying descriptive or inferential statistical methods to analyze data from multiple sources, validate results, identify trends or patterns, and develop findings, reports, or recommendations.
  • Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, validate, analyze, visualize, or document structured or unstructured data for data science projects.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, prescriptive analysis, or exploratory data analysis, to evaluate data, models, programs, or operations and make projections or recommendations.
  • Creating and presenting reports, dashboards, visualizations, written summaries, or presentations that explain statistical or technical methods, findings, limitations, or recommendations to managers, stakeholders, customers, or project teams.

SPECIALIZED EXPERIENCE GRADE 13: In addition to the basic requirements above, to be eligible for this position at the GS-13 level, 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. Specialized experience for this position includes experience performing all the following:
  • Independently planning and carrying out data science or statistical analysis projects by defining analytic questions, selecting data sources or methods, analyzing structured or unstructured data, validating results, and developing findings or recommendations.
  • Developing or applying statistical, machine learning, operations research, or other data science methods to evaluate programs, operations, compliance, or organizational performance, for example forecasting, predictive or prescriptive modeling, optimization, natural language processing or text analytics, graph or link analysis, or exploratory data analysis.
  • Using programming, query, scripting, or analytic tools, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to prepare, transform, document, analyze, and visualize data for data science projects.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Documenting analytic approaches, assumptions, limitations, validation results, success measures, or key performance indicators, and presenting technical findings or recommendations to managers, stakeholders, customers, or cross-functional teams.

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

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