Applied Science Architect

Partners with science, engineering, and product leaders to develop strategies to identify and address business and product needs, and leads the integration, alignment, prioritization, and execution of research and development strategies to develop innovative products and services. Advises on the design and execution of research end-to-end applied research: surveying state of the art, preparing high-quality datasets, running POCs/experiments, and designing, training, and optimizing ML/AI models and solution architectures. Drives cross-functional initiatives to deliver and deploy solutions into production, and ensures delivered solutions successfully solve product and/or business problems. Participates in the research community by publishing and presenting research findings and serving as a keynote speaker.
Minimum Job Qualifications
Education and/or Experience:
18 years of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field
OR
Bachelor's Degree in Mathematics or Statistics, Computer Science, Data Science, Physics, or related field AND 14 years of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field
OR
Master's Degree in Mathematics or Statistics, Computer Science, Data Science, Physics, or related field AND 12 years of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field
OR
Doctorate in Mathematics or Statistics, Computer Science, Data Science, Physics, or related field AND 10 years of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field.
Job Skills:
Same skills as prior level.
Lab/Research Group Experience:
3 years of experience overseeing a lab and/or research group.
Programming Language:
10 years of experience in applicable programming language.
Preferred Job Qualifications
Education and/or Experience:
19 years of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field
OR
Bachelor's Degree in Mathematics or Statistics, Computer Science, Data Science, Physics, or related field AND 15 years of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field
OR
Master's Degree in Mathematics or Statistics, Computer Science, Data Science, Physics, or related field AND 13 years of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field
OR
Doctorate in Mathematics or Statistics, Computer Science, Data Science, Physics, or related field AND 11 years of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field.
People Leadership / Management Experience:
3 years of experience in a leadership role with or without direct reports.
Budget Experience:
3 years of experience working with operating budgets and/or project financials.
Academic Writing and Publication:
6 year of experience creating publications (e.g., white papers, peer-reviewed conference or journal articles).
Key Responsibilities
Solution Identification:
–Partners with science, engineering, and product leaders to develop strategies for Oracle to identify and address strategic business and product needs related to the use of machine learning (ML) and/or artificial intelligence (AI).
–Leverages market trends and subject matter expertise to identify and understand problems that will make an impact across Oracle and the industry. Builds and communicates an understanding of the potential risks and rewards associated with problems to senior executives.
–Sets science quality standards for the Line of Business (LOB), and leads the end-to-end execution of science strategy to address product and/or business problems.
–Leads the integration, alignment, prioritization, and execution of research and development strategies to develop innovative products and services.
–Drives and integrates emerging industry developments into solution strategies and proposes new directions for the business.
–Identifies opportunities to apply delivered solutions across a line of business.
Solution Development – Applied Research:
–Leverages results of proofs-of-concept (POCs) or research experiments to communicate the risks, rewards, and strategic impact associated with innovative solutions and gain buy-in for applied research strategies from executive stakeholders.
–Consults on the establishment of Oracle-wide standards for the selection and preparation of datasets for applied research. Ensures that high quality, comprehensive datasets are used across the organization.
–Advises on the design and execution of innovative research programs on new theories, tools, and methodologies to transfer and apply state-of-the-art technologies into products and services or make advancements in the field.
Solution Development:
–Informs standards for the design, development, and optimization of ML and AI technologies, such as model training/fine-tuning and computation optimizations.
–Drives the use of best practices for the architecture of ML and AI solutions, such as data, model, training, and evaluation.
Solution Development – Articulating Research Insights:
–Identifies meaningful insights from highly complex data and metadata sources from analysis and experiments.
–Interprets and communicates insights and findings throughout Oracle.
–Leads the creation of patents, white papers, or other technical documentation related to applied research outcomes.
Solution Delivery – Coding and Documentation:
–Evaluates, offers guidance on, and serves as a resource across the team on high-complexity code and properly maintains and organizes existing codebase.
–Identifies improvements and updates to best practices for version control, code review, and code delivery/deployment and guides less experienced team members.
–Builds, maintains, and reviews professional documentation for technical processes (experimentation, data collection and analyses, model building).
–Owns the repository for the team.
–Leverages tools to improve coding and documentation productivity.
Solution Delivery:
–Drives cross-functional initiatives to ensure the successful and timely delivery of solutions and integration of services.
–Directs cross-functional teams to deploy solutions into production environments.
–Leads the peer review of solutions prior to delivery.
–Coordinates the delivery of solutions with applied science team members.
–Ensures delivered solutions successfully solve product and/or business problems.