Dinesh Arockia samy

Life is full of challenges, from waking up to go to work to delivering mountainous milestones. Businesses also are not excluded from challenges in all segments of endeavors. As regards difficulties in business technology, a versatile technology expert is needed to navigate these challenges and proffer effective solutions for business benefits. Fortunately, that is the call I answer for organizations. 

I am a seasoned technology leader with a legacy in leveraging up-to-date technological know-how to pilot the enterprise technology needs and wants to businesses’ desired destination. I have a Master of Science degree in Data Analytics and a MuleSoft Certified Developer credential, demonstrating my proficiency in various technologies, tools, systems, and programming languages.

My robust capabilities in Data science / Machine learning, Generative AI / LLMs, Business process management / Master data management make me stand out and fuel my direction in developing custom technical solutions to address business requirements, solve complex problems, and improve overall performance.

I have made marks and formidable footprints while architecting and deploying technical solutions for organizations to thrive. A few of my accomplishments are:
✅ Implemented Gen AI solutions from scratch for Morgan Stanley wealth management
✅ Designed and implemented client centric process and data workflows for Morgan Stanley / Merrill Lynch 
✅ Spearheaded the conversion of millions of accounts in company mergers, processing corresponding data attributes.

Specialties:
Solutions Integration | Gen AI | Machine learning | Data Integration, Merging & Synchronizing | Master Data Management | Project Leadership | Technology & Business alignment| Cross-functional Collaboration | Issue De-escalation & Resolution

Technology Vice President in Morgan Stanley from Apr, 2015. 

Responsibilities:

• Played a key role in company mergers projects and integrations, leading the E-Trade to MS integration initiative.
• Attained a 20% growth in net new assets for financial advisors by deciding the next best action through ML based platforms.
• Set up end to end RAG based data pipeline for un-structured data and generating insights by using embeddings and LLM.
• Collaborated with product managers, data scientists, software engineers, and stakeholders to understand business goals and determine AI / ML requirements.
• Implemented AI based auto healing using Gen AI / LLMs to potential errors and thereby reduced manual efforts from Production support, incident management teams and other support stakeholders.
• Built ML models for Fraud detection and FA lead scoring.
• Built an Automatic workflow Agent for dynamic and spontaneous tasks using LLMs.
• Streamlined business rules management for client and account data by formulating a centralized repository, reducing anomalies, and maximizing convenience for business users to access technical rules.
• Reduced data governance costs by ~30% and ensured a single source of record for all Wealth Management systems by employing Master Data Management systems to consolidate redundant demographic data capture.
• Led the successful conversion of 1.7M brokerage accounts from E-Trade to Morgan Stanley, processing 1.7B data attributes through a conversion strategy to prevent legacy process dependency.

MS in Computer information systems with Data science as Major

Boston University