> Markdown version of [/jobs/ext/542633-sr-data-scientist](https://www.wearedevelopers.com/jobs/ext/542633-sr-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Data Scientist - **Company:** Excelsior University - **Location:** Albany, NY, United States - **Experience:** Expert - **Salary:** $85,000.0 - $95,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Cloud Computing, Data Cleansing, Python (Programming Language), Machine Learning, Natural Language Processing, SQL Databases, Feature Engineering, Large Language Models, Prompt Engineering, Information Technology, Performance Monitor - **Published:** June 12, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=20f1288c5be4c815 ## About the Role Do you have experience in Tooling?, Qualifications: To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. * Master's degree in data science, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field. * 2-3 years experience of 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. ## 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., * 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. * Partners 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. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [RPA in the Public Sector](https://www.wearedevelopers.com/videos/86-rpa-in-the-public-sector) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Anomaly Detection - Using unsupervised Machine Learning for detecting anomalies in customer base](https://www.wearedevelopers.com/videos/6-anomaly-detection-using-unsupervised-machine-learning-for-detecting-anomalies-in-customer-base) - [From Global Capability Centers to AI-Powered Command Centers](https://www.wearedevelopers.com/videos/100096-from-global-capability-centers-to-ai-powered-command-centers) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Got AI ideas but no money? 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