United States
Robert is an Information/AI Architect - AI Generalist - who is “hands on” with Service/Data Modeling while applying the Industry Standards. He can bridge the gap between your company’s Business and IT initiatives while ensuring C-level understanding for tactical and strategic decision making. Robert is a specialist in the architecture, design, & development (ML/DataOps) of Cloud based Lakehouses for MDM:DWH:CRM integrations with SOA:API:microServices for AI:BI:BusinessRules augmentation. Unstructured, SemiStructured, & Structured Data integrations with Taxonomies:Ontologies, Vocabularies:Catalogs:Dictionaries and Canonical:Logical:Physical models are his forte. The Data Sciences/AI have been his focus since grad studies where Robert has applied techniques from MachineLearning, Artificial/Computation Intelligence, BIGgoodData, and Data Mining. Robert is a pioneer in the application of Computational Intelligence for Financial Engineering and Economics (CIFEr) with emphasis on Advanced Algo Trading strategies and Risk Management. Robert's research abilities coupled with his work experience, give him an outstanding ability to evaluate and apply new technologies and products. Robert has over thirty years of experience in designing, developing, and maintaining information technology systems while applying the needed data governance mechanisms. Project:Product management, Team:ThoughtLeadership, and mentoring have been an integral part of Robert's experience. He has an extensive background with operating systems, communications, databases, AI, and the internet. Robert’s domain knowledge cuts across the Financial, Pharmaceutical, HealthCare, Insurance, Energy, HighTech, and Agriculture industries. Specialties: AI/Data Sciences/ML - Information/AI Architecture – AI Generalist - Modeling(BPMN, Rules, TaxonomyOntology, VocabularyCatalogDictionaries, CanonicalLogicalPhysical) – SOA>Web:API:REST:micro>Services – IndustryStandards – DataMining - KDD - CIFEr:AI – TradingSystems – RiskManagement – CRM:MDM:DWH - LakeHouse - BI – BusinessRules:BPM – theInternet/SemanticWeb – Cloud - Graph – BigData - SemanticAI - SEO with AI - Agile- AI:ML:DataOps - DataLiteracy - ResponsibleAI - EnterpiseAI - ExplainableAI
Robert's Consulting Assignments: -- DBmind (Jan'14-now) {8 research projects} •Information/AI Architect & BigDataScientist -- Merck{10 projects} •MRL:GCTO-DataScience Data Scientist (Jan’26-now) •MRL:EPI:RWDEx-ProductArch/BA(Jan’24-Dec’25) •MRL:GMSA-SEOviaAI-ProductArch/BA(Jan’23-Dec’23) •MRL:GMSA-Veeva-ProductArch/BA(Jul’22-Feb’23) •MRL:GMSA-Rev/Ops- ProductArch/BA(Jul’22-Dec’22) •MRL:EPI:ModelRepo-ProductArch/BA (Sep’21-Jul’22) •HH:ProductArch:NextGenPricing-GMAX(Jan’21-Aug’21) •MMD:Taxonomist/Rules Arch/Modeler&DataScientist (May'16-Oct'16)(Aug'13-Jun'14) •MRL Info/MDM Arch&Modeler (Jan'12-Aug'13) -- Novartis - {3 projects} (bus side) •Commercial Pharma AI/ML MDM:DQ Rules - ProductManager/OwnerBTA (Jan’20-Dec’20} •Commercial Oncology MDM/DWH InformationArchitectBTA (Nov’18-Dec’19) •CTMS InformationArchitectBTA (Nov’16-Aug’18) — Barclays (Jun'15-Mar'16) •CCAR InfoArchitect & BPMN Modeler -- Prudential (Jan'15-Jun'15) •Enterprise/MDM DataArchitect & Modeler -- CenterlightHealthSystems (Sep'14-Dec'14) •MDM/InforArch -- CreditSuisse - {4 Projects} •Client On-Boarding ServiceModeler and SOA Architect (May’11-Dec’11) •Equity Shared Service/Trading Technologies - InfoArch and Modeler. (Jun’10-May’11) •Trading Horizontal - PrimeServices ProductLine Rep and InfoArch (May’09-May’10) •InfoEnterprise Architect (Oct'08-Dec'08) -- XBRL & LegalXML (Jan'09-Apr'09) •Information/Rules XML Arch -- CitiBank (May'07-Sep'08) •Capital Markets InfoArch/Modeler -- Bank of TokyoMitsubishi UFJ (Mar'07-Apr'07) •KYC Arch/Developer -- JPMorganChase - {4 projects} •CHF>MortgageSecurities InfoArch/Modeler (Jan'05-Feb'07) •OpRisk InforArch/Modeler (Mar'03-Dec'04) •Global Credit Risk DWH Arch/Developer (Dec'99-Dec'01) •Chase>AI/DataMining/DWH Arch/Modeler (Dec'96-Apr'97) -- BessemerTrust (Jun'02-Feb'03) •CRM ETL InforArch/Developer -- DeutcheBankSecurities (May'97-Nov'99) •Fixed Income Middle Office-InfoArch/Developer -- J&J (Jun'96-Nov'96) •DWH Arch/Modeler
• AI/ML tools used: KNIME, DataIku, Alteryx, SAS, SPSS, Weka:RapidMiner:Pentaho, SageMaker, DataLogic/R (also Prolog, Lisp, Python, R, Perl) DataViz:SGI:Mineset,Qlik,Tableau,Spotfire With:AWS,Azure,Databricks,MLflow,etc. With:Anaconda:Jupyter,PyCharm,VScode,Github • AI based SEO:InsightfulSearch:Coveo/Elastic/OpenSearch/GenAI/ChatGPT/langChain/VectorDB • XAI reviews for legal and compliance:reg and governance due diligence. For paramount decisions>>>why build a model you are not able to understand? Build an Interpretable one instead!!! • Salesforce Einstein chatbot investigation with SemanticAI augmentation for healthcare. Also AWS:Lex, NLP/LSTM/BERT/Tensorflow, IVR to IVA, NLUconversationalAI. • Databricks MLflow experiments review with Pandas,SciKit,Koalas,NumPy,SeaBorn,PySpark,PyTorch. Worked with parquet file ingestion to delta tables in the metastore with DBC based notebooks. Spark dataframe pointers were converted to Pandas raw data. Setup feature set with Target and schema. Applied regularization with label and One Hot Encoding. Attached Notebooks to the cluster with the model registry. Evaluated the various scores and experiments. • MDM Integrations with AI capability model mapping for an EA strategy and roadmap. • Examined software products for the Data Visualization of Systemic Risk • Associate Editor for the Computational Intelligence Magazine/AI for the IEEE CIS • External Thesis Advisor for an AI related Master’s Thesis. • Reviewing papers for the IEEE CIS/AI related Conferences. • Participated on a startup of a virtual AI University as their Industry Liaison/Adjunct Prof. We did not get the state level approval but I hope the founders do give it another go - in another state. • Researched Smartlogic/Marklogic integrations with FIBO – FinancialIndustryBusinessOntology & RDF/SKOS:W3C & BigData - OpenData - Linked Data. • HarmonyAshOhdsiRWE with AI emphasis. • Investigated Data Wrangling/Munging (Trifacta/Alteryx) products with Big Data. .
It's exciting that Novartis has publicly announced some AI initiatives being adopted. This project has embarked on a great journey to establish a Dataiku AI/ML analytical capability on top of a solid framework. ThIs entails a well defined speedy Matillion ingestion layer that uses the latest big data technologies. This data is processed into a cloud Snowflake based data warehouse with data lake extensions (Lakehouse). A crucial component to all of this is superior DataQuality with optimal checks showing the data health via its data pipeline processing layers with data lineage, search catalog and BPM. These advanced DQ checks/rules are visually monitored with the appropriate alerts while being auto configureable. All end users of the data will have the comfort to know the health of their data. It’s important to know as they build out their AI/ML based models with the training sets needed. The needed hyper-parameters can be set while knowing where your data inconsistencies originated. Model(Data/Concept) drift will be easier to ascertain with validation efficacy. Incorporation of false positives/negatives model controls are paramount. Multiple imputation fixes can be more easily conceived with the unhealthy data identified. Critical problems can be pushed back to the originating source systems (MDM:CRM:Salesforce:Veeva/IQVIA/Symphony/MedPro/Concur/etc) for data steward fixing. This was an agile/Jira based release and we also gathered requirements for the next gen MDMs:(Customer/Product) techTags:Salesforce:Veeva,CRM,MDM,DWH,Lakehouse,Siperian,EBX,Snowflake,BRMS,BPM:RPA,Neo4j,Balsamiq,Qlik,SNOW,AWS,Azure,Airflow,ControlM,Boomi,StreamSets,AAD:SSO,Matillion,Jira,Agile,CICD,Git,SAFe,iServer,URS.FS,SDS,QC:ALM,MicroServicesAPIpython,K8,DataIku,Exadata,AIX,SAS,Alteryx,CDH:Hue,Hive,S3,SAP,TestPlan,Postgres busTags:Reps,FF,FRM,HCP,HCO,IC,Targeting,CP,NDC,LiquidHub,MedPro,ModelN,Symphony,IQVIA:IMS:NSP:DDD,oneKey,Veeva,NPPA,SLN,Centris,KOL,MSL,KPI:DataLiteracy,APLD,21CFRp11
I lucked out again with another great project in Oncology on the Commercial business side with Data Strategy and Services (DSS) overlooking not only their HCP/HCO MDM systems but also their CustomerDataWarehouse and MasterProfiles used for their Goaling, Call Plan/Targeting and IncentiveCompensation. The MPs for both ZipTerr are analyzed with both SAS:Alteryx. I also managed their Product MDM system(PRIMO) which will be upgraded. Crucial integrations with our CRM:Salesforce:Veeva were enhanced. The leadership focus and direction was impeccable. Thank you Mimi&Julia. The next gen MDM system was totally fascinating and it was awesome being part of that pre-work and analysis with the needed data cleanup. Optimizing the merge rules while improving the Data Steward processes were paramount. Working with our ScrumMaster with Jira Next-Gen was enlightening. Our extended team were experimenting with DataViz and AI/ML capabilities too. Also, I love how the speaker programs and “lunch and learns” work and how MDM/DWH/CRM give them the necessary data to host these events. I'm mesmerized by all of the “moving parts” in order to make these events happen. Working on upgrading this software and processes will be a boon for Novartis. Also supported the Commercial operations for sales and new product launches. As the Business/ProductOwner/BTA - I reviewed and approved numerous SNOW tickets and project requirements, functional specs and test cases. Compliance® reporting – sunshine reports were enhanced and monitored. techTags:Salesforce:Veeva,Concur,Siperian,EBX,Reltio,CRM,MDM,DWH,DataLake,Exadata,AIX,Tableau,SAS,Alteryx,SAP,Boomi,Synergistix,SNOW,AWS,Azure,CDH:Hue,ETL,Jira,TOGAF,ITIL,Agile,SAFe,iServer,Git,FS,SDS,QC:ALM,CSV:TestPlan,ISO,W3C busTags:Reps,FF,FRM,HCP,HCO,IC,Targeting,CP,NDC,LiquidHub,Medpro,ModelN,Symphony,IQVIA:IMS,SLN,NSP,DDD,Veeva,NPPA,Centris,KOL,MSL,APLD,NPI,Affiliations,DIA,ICH:EMA.,GDPR:PII,NIH,DEA,SunshineReports,ToV,HITECH,HCOS,HarmonyAshRWE. 1b:oneKey
In 1987 my Dad passed away from cancer. This diabolical disease has robbed so many! During my grad studies - I promised myself I would join the fight against cancer in one way or another. This project at Novartis made me feel like I was contributing along with my apheresis/blood donations and being on the bone marrow registry. Efficient clinical trials are paramount to curing cancer. Having the proper CTMS software is necessary from the beginning with a solid Clinical Dev Plan(CDP) right to the end with a successful Clinical Study Report (CSR). Proper alignments are needed for the Portfolio/Program:Project:Study/Trial across all relevant countries with sites involving both personnel and patients. Tracked milestones/events will vary across the study type with the first to last patient visit. Finding that billion $ molecule and having it cure cancer is a mighty journey. Having efficient clinical trials across the Pharma Industry will save billions while finding a cure faster. It was a magnificent project upgrading this CTMS system(Parexel:Impact v3.4 to 14.7) with new software and processes for the Darwin/Stride program. It was an honour being their Information Architect/Business Technical Architect while ensuring the data liaised to a central data hub/Data Warehouse with MDM initiatives and governance mechanisms for their advanced analytics programs. Also thanks to Brett,Debanjan,Shiji: working with you guys and all others was awesome. One of my ultimate dreams is to apply my grad studies research in AI/ML to help cure cancer and destroy this ugly disease from the face of this earth. techTags:CTMS:Parexel:IMPACT,EDC,EA,TOGAF,ITIL,iServer,XMLspy,Erwin,XSD,API,SOA,Documentum,SNOW,Boomi,Azure,Jira,Agile,URS,FS,SDS,QC:ALM,BO,IDQ,EBX5,Oracle,Git,Eclipse,Toad,ISO,W3C,S42,TestPlan,AAD:SSO:NIST,Axway busTags:CTM,FRM,CRO,CRA,IIT,ARM,MedDRA,,CDISC:BRIDG,MediData,IDMP,NDC,CDP,IDP,FPFV,COV,CSR,DIA,ATOM:AMPL,RWE,ICH:EMA,FDA,GxP,SOP,SIPOC,GDPR:PII,NIH,DEA,CSV,KOL,MSL,21CFRp11
AI/ML/Data Science: • Investigated a Decision Support System optimizing appliance claim/repair and scheduling for a Home Appliance Insurance/Warranty company. Root-cause analysis combined with cost efficiency were incorporated. An in-house Rete Algorithm was compared to a JBoss Rules approach. Future recommendations were proposed. • Reviewed numerous papers applying Topic Modeling to Big Data and Data Visualization and a paper integrating Fuzzy Logic with XBRL. • Investigated a CART Decision Tree system for a Mortgage and Consumer Loan Servicer to analyze and predict loan prepayment & default. • Researched a rules based CBR solution to a financial problem. • Investigated IBM Watson's applicability to a financial problem. • Chaired the IEEE CIS/NeuralNetwokCouncil CFE TC & CIFEr conferences in CapeTown, Athens, Hawaii, & Bangalore. CIFEr - Computational Intelligence for Financial Engineering and Economics. MDM/Rules Architect/Modeler: • Reviewed the current state architecture for a Global Wealth Management Prospect/Client Profile System while looking for gaps in their Information Architecture. The main focus was on their Party/Product data with Account linkages. Lack of Governance was a major inhibitor for their systems operations. Data Quality and performance issues needed to be addressed. The Client annual mail out was too onerous for example. FINRA/FDIC/Dodd Franks Reg requirements were examined. The system was Sybase/Java based. Numerous future state options were examined one of which was to use Informatica's ETL/MDM platform. Power Designer was the modeling tool used. • Reviewed a BCBS 239 platform in relation to the CCAR/DFAST policy intersection points. • On the Program Committee while reviewing papers for the International Workshop on Decision Mining & Modeling for Business Processes (DeMiMoP). Attended DMN process modeling presentation while examining its intersections with BPMN. Investigated process/rules/task mining tools with RPA intersections.