About Company
For over 40 years, SAS Institute has been a global leader in analytics software and services. Headquartered in Cary, North Carolina, we empower organizations worldwide to make smarter decisions faster. Our innovative solutions span across artificial intelligence, machine learning, data management, business intelligence, and more, impacting diverse industries from healthcare and finance to government and manufacturing. At SAS, we believe in the power of data to transform lives and drive progress. We foster a collaborative, inclusive, and stimulating environment where curiosity is celebrated, and groundbreaking ideas come to life. Joining SAS means becoming part of a legacy of innovation and contributing to a future shaped by data-driven insights. We are committed to employee growth, offering extensive development opportunities and a vibrant campus culture that supports well-being and community engagement.
Job Description
SAS Institute is seeking a highly skilled and passionate Data Scientist to join our dynamic team in Cary, North Carolina. This is a unique opportunity for talented individuals, including those who require visa sponsorship, to contribute to cutting-edge projects that leverage vast datasets to solve complex business challenges. As a Data Scientist, you will be instrumental in designing, developing, and deploying advanced analytical models and machine learning algorithms that drive critical insights and innovation across our product portfolio and client solutions. You will work closely with cross-functional teams, including product managers, engineers, and domain experts, to identify opportunities, define problems, and deliver robust, scalable data science solutions. The ideal candidate will possess a strong foundation in statistical modeling, machine learning techniques, and programming, coupled with an ability to communicate complex concepts clearly. If you are driven by data, eager to explore new methodologies, and thrive in an environment that values continuous learning and impactful contributions, we encourage you to apply. This role offers the chance to work with industry-leading technology and make a tangible difference in how businesses leverage data.
Key Responsibilities
- Design, develop, and implement machine learning models and algorithms to solve business problems across various domains.
- Perform extensive data cleaning, preprocessing, and feature engineering to prepare large, complex datasets for analysis.
- Conduct exploratory data analysis to uncover trends, patterns, and insights.
- Collaborate with product managers and engineering teams to integrate models into production systems.
- Evaluate model performance, interpret results, and communicate findings to technical and non-technical stakeholders.
- Develop and maintain comprehensive documentation for models, methodologies, and data pipelines.
- Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence, and apply new techniques where appropriate.
- Participate in code reviews and contribute to a culture of technical excellence and best practices.
- Contribute to the strategic direction of data science initiatives within the company.
Required Skills
- Strong proficiency in Python or R for data analysis and machine learning.
- Solid understanding of statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning).
- Experience with SQL and relational databases for data querying and manipulation.
- Ability to work with large, complex datasets and distributed computing frameworks (e.g., Spark).
- Excellent problem-solving skills and a methodical approach to data analysis.
- Strong communication and presentation skills, with the ability to articulate complex technical concepts to diverse audiences.
- Demonstrated ability to work both independently and collaboratively in a team environment.
- Familiarity with data visualization tools and techniques.
Preferred Qualifications
- Master's or Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
- Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices.
- Proficiency with deep learning frameworks such as TensorFlow or PyTorch.
- Experience with SAS products (e.g., SAS Viya, SAS Enterprise Miner).
- Prior experience in industries such as finance, healthcare, retail, or government.
- Contributions to open-source projects or a strong portfolio of data science projects.
Perks & Benefits
- Comprehensive health, dental, and vision insurance.
- Competitive 401(k) plan with company matching.
- Generous paid time off, including holidays and sick leave.
- On-campus amenities including fitness centers, cafeterias, and walking trails.
- Professional development and training opportunities, including access to SAS software and courses.
- Tuition reimbursement program.
- Employee assistance program.
- Relocation assistance and visa sponsorship for eligible candidates.
- Collaborative and innovative work environment with a strong company culture.
How to Apply
Interested candidates are invited to submit their application by clicking the link below. Please ensure your resume highlights your relevant experience, technical skills, and any projects you’ve worked on.