Accelerate use of AI for continuous improvement and new product development

CORPORATE PROFILE: A customer service company with 15,000 employees.RESPONSIBILITY PROFILE: I report to the CEO with shared responsibilities for team budgets and shared company revenue goals managing 45 employees with five direct. I am responsible for defining the AI roadmap for conversational AI, maintaining a world-class AI solutions team, leading LLM use cases, and acting as the company's public face for AI.CUSTOMER ENGAGEMENT• The company required an AI leader for a successful IPO acquisition. I developed an AI roadmap and partners, libraries, and tools, then enhanced the system, created value propositions, and developed communication metrics. This strategy was declared Best Practice, effectively completed data collection and cloud implementation, improved customer satisfaction, and heightened brand awareness.ML OPERATIONAL OPTIMIZATION / DATA MIGRATION• To reduce processing costs, the COO charged me to close data centers, refocus GCP pipelines, and transfer products. Within 12 weeks, formed a strategy and gained approval, then migrated AI models from the data centers, oversaw platform integration, tracked incident reports, ensured algorithm efficacy, and navigated buy-in from teams and clients. This strategy was declared SOP, as it reduced processing costs by $600k while eliminating redundant data centers.AI / MACHINE LEARNING• Personally discovered an opportunity to use a large language processing model to improve business efficiencies. Over 8 months, analyzed research papers on the topic, devised a novel student/teacher methodology, assessed security limitations, and resized the model to fit business needs. These efforts improved intent prediction, led to enhanced containment, and reduced the model size by 13% without declining results; as a result, the model’s usage became an SOP. The model was developed using GPT2 prior to the release of chatGPT3. Since then, we have been working to integrate Generative LLMs into our production workflows.

CORPORATE PROFILE: A $2.64B publishing company with 8,600 employees.RESPONSIBILITY PROFILE: I reported to the COO with a $10M OPEX and 110 employees with eight direct. I was responsible for modernizing their data sciences pipelines, strategy, and vision, bringing ML & AI to their data platforms, optimizing their data operations, and acting globally as the face of data science.OPERATIONAL AUTOMATION• To automate data collection (chemical information), I planned a strategy, and then led execution over 6 months, which included hiring third-party partners for chemical entity extraction. Within the following 90 days, I analyzed workflows, created new models, and implemented/tested various in-house products. Within 6 months, these ML models increased chemical entity extraction from journal articles by 35X (from 450 articles/year to >16,000), which realized millions more chemical entities and their properties to be included in the database, as well as a 20% cost savings per Anum ($1M).TALENT ACQUISITION• The company needed qualified data science personnel to meet the need for modernizing workflows. I reached out to the University of Amsterdam to find potential internship candidates. Identified projects, hired select students, and promoted interns based on reviews/performance data. These efforts established a steady pipeline of 10 interns/year, many of whom moved into full-time positions. Resulting in a very low attrition rate, much less for the data science group than the company overall.STRATEGIC PLANNING• A matrix was created to integrate a data science team into product and engineering workflows. I collaboratively created a platform within 8 months using a variety of novel methods to isolate and display funding information for ‘quick-viewing’ of research product outputs. This enabled a more efficient pipeline, was added to the market suite, and effectively led to two academic publications and an approved patent.

ACQUISITION INTEGRATION• Sought to identify relevant technology and engage in technical due diligence as Elsevier acquired several companies throughout its tenure. In one instance, a platform (Mendaley) sought to encourage traffic and migrate content onto a paid site (Science Direct). Developed a novel approach to migrate the data, organized teams, directed efforts to increase SEO and related article searches, and managed ongoing integration efforts to accomplish required integration into the company’s workflows and systems. Over 18 months, completed integration, resulting in a 15% increase in traffic for the paid platform.AI / ML INTEGRATION• I was recruited by the COO to transform and modernize the company’s content process estate from manual to automated using AI / ML. Collaboratively with the CEO, assessed current company SOPs, identified gaps, acquired buy-in, crafted client-facing messaging, hired/mentored data scientists, and evangelized a culture of collaboration. Over five years, the company hired over 50 data scientists, and these efforts established Elsevier as one of the leading adopters of AI / ML tools; these tools are still used by the company today.COMMUNITY INVOLVEMENT / INNOVATION / BRANDING / IMAGE DEVELOPMENT• As the Head of Innovation, the global technology leader advised governments on AI systems and privacy while supporting technological advancement in underserved markets. Served on an EU AI committee with Tony Blair, correlated with the company as a major sponsor of the Einstein Forum in Africa, serving as a judge for an event regarding the best new innovative companies, with five African presidents in attendance. These efforts supported innovation and community connections, strengthening the company’s reputation.

Innovative Analytics advises clients on policy and strategy surrounding their analytic needs. With my technical background in computational linguistics and social media analytics, I help our clients in the area of Data Sciences with a focus on social data and human language technology.

CORPORATE PROFILE: A $1.6B national lab working closely with the government with 4,922 employees.RESPONSIBILITY PROFILE: I was responsible for fostering a research program in AI with a focus on computational linguistics, structuring client-funded research, and establishing PNNL as a scientific leader in AI and ML.AWARD-WINNING DATA COLLECTION / TECHNOLOGY INNOVATION / INTEGRATION / BUSINESS DEVELOPMENT• As a DOE S&T Lab, I provided technology to multiple government agencies. All programs were self-funded and required understanding clients' needs, identifying scientific solutions, and implementing them. This required a deep understanding of the government contracting process, working across multiple agencies, and being able to hire staff to support the projects.PROGRAM MANAGEMENT• With the goal of creating an innovative program in social media analytics, I began with a minor $10K contract and grew into a $5M multi-agency program. I worked with government leaders to transform open-source data into usable intelligence utilizing Web 2.0 technologies. Established background knowledge in computational linguistics to allow new technologies and form essential industry partnerships. Personally received multiple awards, including the 2006 Early Career Scientific Achievement Award and the IEE Young Engineer recipient award two years in a row.

In addition to conducting research in Prosody and Speech Processing, I helped developed SUNY Buffalo's MS program in computational linguistics.

I worked with Eugene Charniak and Mark Johnson in the general area of computational linguistics. In addition to teaching courses in corpus linguistics and prosody, I investigated using prosodic features to aid statistical parsing.