Data Scientist
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Job Description
Principal Data Scientist designing and implementing AI systems for business decision making. Collaborating with various teams to provide innovative data solutions.
Responsibilities:
- Design and implement scalable and reliable approaches to support or automate decision making throughout the business
- Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear
- Acquire data by building the necessary SQL / ETL queries and import processes through various company specific interfaces for accessing S3, RedShift, and Spark storage systems
- Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies
- Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks
- Validate models against alternative approaches, expected and observed outcomes, and other business defined key performance indicators
- Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production
- Implement and deploy state of the art machine learning algorithms under Gen AI, build prototypes, troubleshoot customer issues, and explore new solutions
- Interact closely with customers and with the academic community to drive innovation and deliver tailored data science solutions
Requirements:
- 10+ years of data scientist experience with a proven track record of solving complex business problems through data science
- Bachelor’s degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field
- Competency in data querying languages (e.g. SQL) and scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.)
- Experience with statistical models (e.g., logistic regression, supervised learning approaches) and a solid foundation in machine learning methods
- Excellent communications skills with non-technical executive audiences, with the ability to translate complex models and findings into clear, actionable insights
- 1+ year of hands-on experience with AI/ML technologies and modern machine learning frameworks
- Demonstrated leadership and technical mentoring experience across a team or organization
- Strong stakeholder communication skills with the ability to translate technical depth across audiences
- Demonstrable, day-to-day usage and expert knowledge of AI-forward coding tools such as Claude and Cursor
- Excellent problem-solving skills and the ability to navigate highly ambiguous technical and business challenges with sound judgment
- Experience with advanced machine learning frameworks and cloud-based data science platforms is a plus
Benefits:
- Health insurance
- Professional development opportunities
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