Jayesh Prakash Gupta, Ph.D.

Architected and implemented scalable frameworks for deploying production-ready AI models on leading cloud platforms (Snowflake, AWS), significantly enhancing operational efficiency and model reliability.

Developed and managed an end-to-end MLOps pipeline for time series forecasting, optimizing model selection (LSTMs, Prophet, SARIMAX) and ensuring robust performance monitoring for cloud-based data applications.

Conceptualized a high-level architecture for a new data platform, leveraging Microsoft Azure and SAP services to establish a robust and scalable data infrastructure for future growth.

Facilitated client-centric AI discovery workshops, identifying high-value AI opportunities, and collaborated with cross-functional teams to translate them into actionable plans, including design and prototyping.

Applied proven expertise in data operations, including storage (SQL, NoSQL, cloud), processing (batch, stream, ETL, ELT), version control, security, visualization, and big data, ensuring data integrity and accessibility.

Contributed as a core team member of Capgemini Nordics – GenAI Center of Excellence (COE), advancing organizational capabilities in Generative AI and thought leadership.

Collaborated closely with senior leadership, clients, and the development team to facilitate data-driven decision-making through the identification and continuous monitoring of key performance indicators (KPIs).

Identified and developed new business use cases for process optimization, leveraging ML and AI for the new Kalmar Onwatch 2.0 Service, enhancing operational efficiency and predictive maintenance capabilities.

Designed, developed, and maintained robust data pipelines and interactive dashboards using Python (Pandas) and Tableau, providing actionable insights for internal and external stakeholders based on diverse logs.

Engineered and deployed project reporting systems to automate business processes using Google BigQuery, Google Data Studio, and PowerBI, improving data accessibility and reporting efficiency.

Served as a key contributor to the New Service & Product Development team, responsible for developing the new Kalmar Remote Service (KRS) based on the AWS OpenSearch/Elasticsearch (ELK) stack.

Demonstrated strong collaboration skills, working seamlessly with cross-functional teams across five continents to achieve project goals and foster global alignment.

Led primary research in Data Science, NLP, Business Models, Service Design, IIoT platforms, and Industry 4.0, contributing to academic advancement and practical applications in emerging technologies.

Collected, cleaned, and analyzed extensive datasets, including 80 million tweets and 400,000 crowdfunding projects, using API and data scraping for comprehensive social and market insights.

Implemented diverse data analysis techniques, including statistical analysis, machine learning (Random Forest Regression, XGBoost), NLP (NLTK), and network analysis (NetworkX) using Python and R.

Visualized complex research data using Python (Seaborn), R, Tableau, Gephi, and PowerBI, effectively communicating findings to academic and industry audiences.

Conducted rigorous Quantitative and Qualitative research, including hypothesis testing, A/B testing, surveys, market research, and interviews, to validate research models and insights.

Gained hands-on experience with DevOps technologies (Dockers, Kubernetes, FastAPI) for efficient deployment and management of research prototypes.

Interpreted data using descriptive, predictive, and prescriptive analysis to provide actionable insights and strategic recommendations.

Collaborated with Subject Matter Experts from various domains on multiple research projects funded by Business Finland, Academy of Finland, and the EU, delivering insights to industry partners (e.g., Beckhoff) and academic institutions (e.g., Copenhagen Business School).

Served as a researcher on an Academy of Finland-funded project (COBWEB), focused on enhancing knowledge work and co-creation through Big Social Data Analytics.

Conducted exploratory data analysis on business event-related social media data using Python, R, and social network analysis, culminating in a master's thesis and a research conference paper.

Designed and delivered engaging exercises for two university courses (Data & Information Analytics; New Knowledge - Creation & Tool), improving student comprehension and practical skills.

Supported academic instruction and project coordination, ensuring timely progress and effective dissemination of research findings.

Conducted in-depth interviews with eminent global scholars from industry (e.g., G.E.) and academia, gathering critical insights into the field of Industrial Internet.

Developed innovative value transaction networks for interviewed Industrial Internet platform companies using the Allee Value Network Analysis method.

Authored and presented a comprehensive internal department report, "Making Value of Data, Information & Knowledge utilizing various IIOT Platforms," which was instrumental in securing a EU2020 project and building foundational IIoT research competence.

Contributed to the strategic development of the research group's IIoT expertise, laying groundwork for future projects and collaborations.

Acted as a primary liaison between business stakeholders and the development team for banking domain clients, including Bank of America-Merrill Lynch and Canadian Imperial Bank of Commerce.

Created comprehensive technical documentation and specifications, utilizing UML (e.g., class, use case, interaction diagrams) to ensure clear communication and system design.

Developed robust Java code for critical banking applications, leveraging Relational Databases and Data Mapping Frameworks (e.g., XML) to meet stringent performance and security requirements.

Deployed code efficiently using CI/CD pipelines (e.g., Jenkins) and version control systems (e.g., SVN), ensuring continuous integration and delivery for two different client projects.

Coordinated development activities between onsite client development, offshore development, and quality assurance teams in an Agile environment, optimizing workflow and project delivery.

Supervised the onboarding and training of new team members, enhancing team capabilities and ensuring seamless integration into project workflows.