Job Description:
Proficient in building AI/ML solutions using AWS SageMaker within the AWS ecosystem, with advanced Python scripting skills. Possesses expertise in SQL, along with experience in both research and deployment phases. Familiarity with working in production environments and knowledge of Control-M is highly desired
Leads proliferation of machine learning and artificial intelligence throughout the enterprise. Identifies 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. Leads interactions between analytics, business units and other departments.
ESSENTIAL FUNCTIONS:
20% Leads all data mining and extraction activities and applies algorithms to derive insights.
15% Synthesizes analytical findings for consumption by the teams and senior executives.
15% Leads proliferation of machine learning and artificial intelligence solutions.
15% Applies artificial intelligence techniques to achieve concrete business goals while managing limited resources and constraints around data.
15% Mentors and develops junior data scientists for advanced data analysis.
10% Translates business priorities and creates data science deliverables.
10% Leads implementation of Client/AI/DS best practices for new data products and builds robust and scalable software.
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.
Key Requirement:
Experience building data pipeline for Client and AI models,
Experience optimizing Client/AI Model Code and deployments
Experience with Cloud Platforms, specifically AWS ecosystem, Data Engineering & Data Science Tools
Education Level: Bachelor's Degree
Education Details: Statistics, Mathematics, Computer Science or related field
Experience: 8 years of relevant work experience.
In Lieu of Education
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 communicate effectively and document objectives and procedures., Expert
Ability to leverage a wide variety of data science tools and frameworks., Expert
Ability to support data exploration and data analysis tasks in support of analytics objectives., Expert
Knowledge in model evaluation, tuning and performance, operationalization, and scalability of scientific techniques., Expert
Proficiency in statistical modeling applications., Expert
Proficiency in advanced SQL in multiple syntaxes., Expert
