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Data Science Jobs in Schenectady, NY (NOW HIRING)

Excelsior College

Sr Data Scientist

Albany, NY · On-site

$85 - $95/hr

The data science center leads the development and implementation of machine learning and AI solutions that improve university operations and student outcomes. This role will focus on building ...

Versant Health, Inc.

Senior Data Scientist

Troy, NY · On-site

$150 - $210/hr

This role operates at the intersection of data science, data engineering, cloud analytics platforms, and business strategy, serving as a technical authority and thought leader across complex ...

Versant Health

Senior Data Scientist

Troy, NY · On-site

This role operates at the intersection of data science, data engineering, cloud analytics platforms, and business strategy, serving as a technical authority and thought leader across complex, high ...

Brookfield

Sr P&C Data Scientist

Albany, NY · On-site

Five years of relevant experience in data science, analytics, pricing, actuarial, or related quantitative roles. A master's degree may be considered in lieu of one to two years of experience

Kayla's HR Co

Assistant Manager

Schenectady, NY · Remote

Senior Data Scientist - Machine Learning Specialist We are seeking a talented and innovative Senior Data Scientist to join our growing analytics team. In this impactful role, you will leverage your ...

Munich Re

Data and AI Enterprise Architect

Albany, NY · On-site

Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...

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All JobsData Science JobsData Science Jobs in Schenectady, NY

Data Science information

See Schenectady, NY salary details

$36.3K

$118.8K

$190.1K

How much do data science jobs pay per year?

As of Aug 27, 2026, the average yearly pay for data science in Schenectady, NY is $118,753.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,300.00 and $131,600.00 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 Schenectady, NY?

The most popular types of Data Science jobs in Schenectady, NY are:

What are popular job titles related to Data Science jobs in Schenectady, NY?

For Data Science jobs in Schenectady, NY, the most frequently searched job titles are:

What job categories do people searching Data Science jobs in Schenectady, NY look for?

The top searched job categories for Data Science jobs in Schenectady, NY are:

What cities near Schenectady, NY are hiring for Data Science jobs?

Cities near Schenectady, NY with the most Data Science job openings:

Data Science jobs near you
Infographic showing various Data Science job openings in Schenectady, NY as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $118,753 per year, or $57.1 per hour.

Sr Data Scientist

Albany, NY • On-site

Excelsior College
Education • 1 - 5K employees
Learn more about Excelsior Collegeexternal

$85 - $95/hr

Other

Medical, Retirement, PTO

Posted 9 days ago

Job description

The data science center leads the development and implementation of machine learning and AI solutions that improve university operations and student outcomes. This role will focus on building, deploying, and scaling predictive and generative AI capabilities—including large language model (LLM) applications—to support strategic initiatives across marketing, admission, student advising, and academic affairs. The ideal candidate combines deep technical expertise with strong business partnership skills and a passion for applying cutting‑edge AI technologies in a higher education environment.

Duties and Responsibilities:

  • Design, develop, validate, and deploy machine learning models to improve operational efficiency, decision‑making, and student success outcomes.
  • Build predictive models and intelligent decision‑support tools for use cases such as enrollment marketing, student advising, course engagement, persistence, and retention.
  • Develop and implement LLM‑powered solutions by leveraging popular LLM APIs for university stakeholders.
  • Evaluate emerging AI and machine learning technologies and recommend practical adoption strategies aligned with university goals, governance, and responsible AI principles.
  • Partner with leaders and subject‑matter experts across marketing, advising, academic affairs, teaching and learning, and student success to identify high‑impact opportunities for analytics and automation.
  • Translate complex business problems into data science solutions, including experimentation, feature engineering, model development, and performance monitoring.
  • Collaborate with IT teams to productionize models, integrate solutions into workflows, and maintain scalable, reliable data products.
  • Communicate insights, model results, and recommendations clearly to technical and non‑technical audiences through presentations, dashboards, and written documentation.

Qualifications:

  • Master’s degree in data science, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field.
  • 2‑3 years experience as a data scientist or analyst.
  • Demonstrated experience developing and implementing machine learning models in production environments.
  • Strong proficiency in Python, SQL, and common machine learning frameworks and libraries.
  • Experience with end‑to‑end model lifecycle management, including data preparation, feature engineering, training, validation, deployment, and monitoring.
  • Hands‑on experience with LLMs, natural language processing, prompt design, evaluation, and/or generative AI applications.
  • Familiarity with cloud platforms and modern data science tooling for scalable model development and deployment.
  • Strong analytical, problem‑solving, and communication skills, with the ability to influence decisions through data‑driven insights.
  • Ability to work cross‑functionally and manage multiple priorities in a collaborative environment.

The hiring salary range for this position is $85,000 - $95,000. The hiring salary range above represents the University’s good faith estimate at the time of posting.

Excelsior University offers competitive compensation and a generous benefits package that includes paid time off, retirement, and excellent health insurance.

AA/EOE/ADA

Excelsior University is an equal opportunity employer committed to ensuring all qualified applicants receive consideration for employment without regard to any legally protected characteristic.

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