Sr Data Scientist

Job TitleIdentifies and solves business problems by using various numerical techniques, algorithms, and models in statistical modeling, machine learning, operations research, and data mining. Uses advanced analytical capabilities to support data science initiatives. Communicates across product teams and with customers and educates on artificial intelligence, machine learning, and statistical models. Acting as a liaison and interface between analytics, business units and other departments.Essential FunctionsLeads data mining and extraction activities and applies algorithms to derive insights.Uses data to understand the data profile and its limitations and applies it to business solutions.Collaborates with business units to innovate organizational performance.Explores data patterns using existing data science tools.Translates business priorities to data science deliverables.Implements new data products and builds robust and scalable software.Leads/Guides DS on implementing best practices for projects and applies artificial intelligence techniques to achieve concrete business goals while managing limited resources and constraints around data.QualificationsTo 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.Education Level: Bachelor's DegreeEducation Details: Statistics, Mathematics, Computer Science or related fieldExperience: 5 years of relevant work experience.In lieu of a Bachelor's degree, an additional 4 years of relevant work experience is required in addition to the required work experience.Preferred Qualifications Knowledge, Skills and Abilities (KSAs)Ability to work independently without detailed guidance.Ability to communicate effectively and document objectives and procedures.Ability to leverage a variety of data science tools and frameworks.Knowledge in model evaluation, tuning and performance, operationalization, and scalability of scientific techniques.Knowledge of software engineering principles and practices.Proficiency in statistical modeling applications.Proficiency in advanced SQL in multiple syntaxes.