Job Summary
Individual contributor provides highest level of expertise for AI/ML ,big data technologies, architecture, development, specification and communication of firm's scalable AI/ML transformation from legacy to cloud, advises cross-functional teams in the implementation of a phased approach to moving CNA's On prem model implementation to cloud graduating from near-term "quick wins" to full "self-service" over time. This position involves working in collaboration with Domain Architects, Solution Architects, Digital Architects and Cloud Architects, to ensure it reflects synergies and dependencies with core technology trends and priorities (e.g. Cloud migration, Information Security and Infrastructure), as well as clearly articulates synergies and dependencies across the business units in solidifying target IT application rationalization strategy.
Essential Duties & Responsibilities
Performs a combination of duties in accordance with departmental guidelines:

1. Self-starter and ability to define and hold the big picture while executing on a piece of it, and reduce technical debt while enhancing AI/ML transformation
2. Works with leads to design and architect strategies to unravel legacy Model implementations and define future state
3. Research, recommend, design and develop Predictive model and data architecture to accelerate the CNA's AI/ML transformation
4. Define and architect AI/ML use cases with advanced model techniques, frameworks and cloud technologies
5. Demonstrates opportunities by developing prototypes and/or contributing code, evaluating technologies, and mentoring project team members.
6. Good understanding of AI/ML, big data trends and impact across the industry and how it can enable business transformation and create true value.
7. Ensures the architecture for data transformation journey stays loosely coupled, modular, scalable, extensible and re-usable.
8. Collaborate with superiors and leads to develop and implement the strategic design, acquisition, management, and implementation of an enterprise-wide technology roadmap.
9. Analyzes the technology industry and market trends to highlight potential impact on the business.
10. Ability to define and hold the big picture while executing on a piece of it, and reduce technical debt while enhancing Data Transformation.
11. Researches and evaluates new and/or alternative solutions and technologies to enhance operational effectiveness, reduce costs and/or system risks and increase speed to market.
12. Works with leads to provides in-depth technical consultation to business partners and IT management to ensure development of efficient application systems utilizing established standards, procedures and methodologies.
13. Guides the team that drives implementation of strategic and operational AI/ML objectives with significant impact on the short-term and long-term success.

May perform additional duties as assigned.
Skills, Knowledge & Abilities

1. Knowledge of design and implementing of and/or co-leading Data transformation journey in current or past organization with expertise AI/ML.
2. Experience in implementing and deploying Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, Deep Learning Models)
3. Strong hands-on experience with statistical packages and ML libraries (e.g. R, Python scikit learn, Spark MLlib, etc.)
4. Hands-on experience with a broad range of current deep learning tools (e.g., TensorFlow, Caffee, PyTorch, Keras,) and collaboration environments (e.g. Jupyter notebooks).
5. Experience diagnosing, isolating, and resolving complex issues and recommending and implementing strategies to resolve problems
6. Experience developing strategic initiatives which align with business goals and budget.
7. Demonstrated leadership experience across data, change management, innovation and experience design.
8. Knowledge of design and orchestration of data ingestion into Data Warehouses on cloud (AWS/GCP).
9. Experience building and supporting containerized application technologies including Docker, Kubernetes Familiarity with CI/CD tools and deployment processes
10. Experience working with AI/ML platforms to build, deploy and monitor predictive models
11. Experience working with CPU/GPU/FPGA-based computation.
12. Knowledge of design and implementation of enterprise workflow systems, distributed architecture, intranet/internet architecture, and communication architectures.
13. Senior level knowledge of the system development life cycle, and system and application program development technological alternatives and architecture methodologies for multi-platform environments.
14. Experience data engineering using big data processing and streaming platforms Apache Spark and Apache Kafka or Apache Flink. Other platforms will be helpful
15. Experience working in solutions over any major Cloud provider (AWS, Azure, GCP) is a plus
16. Strong analytical and problem solving skills.
17. Experience developing/following 3-5 year roadmaps outlining the evolution of the enterprise application portfolios from current to future state.
18. Strong and demonstrable hands-on coding experience as AI/ML engineer in their career leading large and complex AI/ML implementations .

Education & Experience

1. Degree in Computer Science, or related discipline, or equivalent experience.
2. Typically a minimum of 10 years of solid, diverse work experience in IT including experience with AI/ML and Data methodologies.
3. Some previous project leadership experience is desirable.
4. Applicable certifications preferred .

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